| blob | 766c59128c74e97d37702c812608c4d65b566dbd |
1 /**
2 * serveccda.js
3 *
4 * @package OpenEMR
5 * @link https://www.open-emr.org
6 * @author Jerry Padgett <sjpadgett@gmail.com>
7 * @copyright Copyright (c) 2016-2017 Jerry Padgett <sjpadgett@gmail.com>
8 * @license https://github.com/openemr/openemr/blob/master/LICENSE GNU General Public License 3
9 */
11 "use strict";
12 var net = require('net');
13 var to_json = require('xmljson').to_json;
14 var bbg = require('oe-blue-button-generate');
15 //var bbm = require('blue-button-model'); //for use set global-not needed here
16 //var fs = require('fs');
17 //var bb = require('blue-button');
18 var fs = require('fs');
20 var server = net.createServer();
21 var conn = ''; // make our connection scope global to script
22 var oidFacility = "";
23 var all = "";
24 var npiProvider = "";
25 var npiFacility = "";
27 // some useful routines for populating template sections
28 function validate(toValidate, ref, retObj) {
29 for (var p in ref) {
30 if (typeof ref[p].dataType === "undefined") {
31 retObj[p] = {};
32 if (!toValidate[p]) toValidate[p] = {};
33 validate(toValidate[p], ref[p], retObj[p]);
34 } else {
35 if (typeof toValidate === "undefined") toValidate = {};
36 var trimmed = trim(toValidate[p]);
37 retObj[p] = typeEnforcer(ref[p].dataType, trimmed);
38 }
39 }
40 return retObj;
41 }
43 function typeEnforcer(type, val) {
44 var validVal;
45 switch (type) {
46 case "boolean":
47 if (typeof val === "string") {
48 validVal = val.toLowerCase() === "true";
49 } else {
50 validVal = !!val;
51 }
52 break;
53 case "string":
54 if ((val === null) || (val === "undefined") || (typeof val === "undefined")) {
55 validVal = '';
56 } else if (typeof val == "object") {
57 validVal = '';
58 } else {
59 validVal = trim(String(val));
60 }
61 break;
62 case "array":
63 if (typeof val === 'undefined' || val === null) {
64 validVal = [];
65 } else if (Array.isArray(val)) {
66 validVal = [];
67 val.forEach(function (v) {
68 validVal.push(trim(v));
69 });
70 } else {
71 validVal = [trim(val)];
72 }
73 break;
74 case "integer":
75 var asInt = parseInt(val, 10);
76 if (isNaN(asInt)) asInt = 0;
77 validVal = asInt;
78 break;
79 case "number":
80 var asNum = parseFloat(val);
81 if (isNaN(asNum)) asNum = 0;
82 validVal = asNum;
83 break;
84 }
85 return validVal;
86 }
88 function trim(s) {
89 if (typeof s === 'string') return s.trim();
90 return s;
91 }
93 function safeId(s) {
94 return trim(s).toLowerCase().replace(/[^a-zA-Z0-9]+/g, '-').replace(/\-+$/, '');
95 }
97 function fDate(str) {
98 str = String(str); // at least ensure string so cast it...
100 if (Number(str) === 0) {
101 return (new Date()).toISOString().slice(0,10).replace(/-/g,"");
102 }
103 if (str.length === 8 || (str.length === 14 && (1 * str.substring(12, 14)) === 0)) {
104 return [str.slice(0, 4), str.slice(4, 6), str.slice(6, 8)].join('-')
105 } else if (str.length === 10 && (1 * str.substring(0, 2)) <= 12) {
106 // case mm/dd/yyyy or mm-dd-yyyy
107 return [str.slice(6, 10), str.slice(0, 2), str.slice(3, 5)].join('-')
108 } else if (str.length === 14 && (1 * str.substring(12, 14)) > 0) {
109 // maybe a real time so parse
110 }
111 return str;
112 }
114 function getPrecision(str) {
115 str = String(str);
116 let pflg = "day";
118 if (Number(str) === 0) {
119 return "day";
120 }
121 if (str.length > 8) {
122 pflg = "minute";
123 }
124 if (str.length > 12) {
125 pflg = "second";
126 }
128 return pflg;
129 }
131 function templateDate(date, precision) {
132 return [{'date': fDate(date), 'precision': precision}]
133 }
135 function cleanCode(code) {
136 return code.replace(/[.#]/, "");
137 }
139 function isOne(who) {
140 try {
141 if (who !== null && typeof who === 'object') {
142 return who.hasOwnProperty('extension') || who.hasOwnProperty('id') ? 1 : Object.keys(who).length;
143 }
144 }
145 catch (e) {
146 return false;
147 }
148 return 0;
149 }
151 function headReplace(content) {
152 var r = '<?xml version="1.0" encoding="UTF-8"?>\n' +
153 '<ClinicalDocument xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="urn:hl7-org:v3 http://xreg2.nist.gov:8080/hitspValidation/schema/cdar2c32/infrastructure/cda/C32_CDA.xsd"' +
154 ' xmlns="urn:hl7-org:v3" xmlns:mif="urn:hl7-org:v3/mif">\n';
155 r += content.substr(content.search(/<realmCode/i));
156 return r;
157 }
159 // Data model for Blue Button
160 function populateDemographic(pd, g) {
161 let guardian = [{
162 "relation": g.relation,
163 "addresses": [{
164 "street_lines": [g.address],
165 "city": g.city,
166 "state": g.state,
167 "zip": g.postalCode,
168 "country": g.country,
169 "use": "primary home"
170 }],
171 "names": [{
172 "last": g.display_name, //@todo parse first/last
173 "first": g.display_name
174 }],
175 "phone": [{
176 "number": g.telecom,
177 "type": "primary home"
178 }]
179 }];
181 return {
182 "name": {
183 "middle": [pd.mname],
184 "last": pd.lname,
185 "first": pd.fname
186 },
187 "dob": {
188 "point": {
189 "date": fDate(pd.dob),
190 "precision": "day"
191 }
192 },
193 "gender": pd.gender.toUpperCase(),
194 "identifiers": [{
195 "identifier": oidFacility,
196 "extension": "PT-" + pd.id
197 }],
198 "marital_status": pd.status.toUpperCase() || "U",
199 "addresses": [{
200 "street_lines": [pd.street],
201 "city": pd.city,
202 "state": pd.state,
203 "zip": pd.postalCode,
204 "country": pd.country,
205 "use": "primary home"
206 }],
207 "phone": [{
208 "number": pd.phone_home,
209 "type": "primary home"
210 }],
211 "race": pd.race,
212 "ethnicity": pd.ethnicity || "U",
213 "languages": [{
214 "language": pd.language,
215 "preferred": true,
216 "mode": "Expressed spoken",
217 "proficiency": "Good"
218 }],
219 "religion": pd.religion.toUpperCase() || "",
220 /*"birthplace":'', {
221 "city": "",
222 "state": "",
223 "zip": "",
224 "country": ""
225 },*/
226 "attributed_provider": {
227 "identity": [
228 {
229 "root": "2.16.840.1.113883.4.6",
230 "extension": npiFacility || "UNK"
231 }
232 ],
233 "phone": [{
234 "number": all.encounter_provider.facility_phone || "",
235 }],
236 "name": [
237 {
238 "full": all.encounter_provider.facility_name || ""
239 }
240 ]
241 },
242 "guardians": g.display_name ? guardian : ''
243 }
245 }
247 function populateProviders() {
248 return {
249 "providers": [
250 {
251 "identity": [
252 {
253 "root": "2.16.840.1.113883.4.6",
254 "extension": all.primary_care_provider.provider[0].npi || "UNK"
255 }
256 ],
257 "type": [
258 {
259 "name": all.primary_care_provider.provider[0].physician_type || "Not Avail",
260 "code": all.primary_care_provider.provider[0].physician_type_code || "",
261 "code_system_name": "Provider Codes"
262 }
263 ],
264 "name": [
265 {
266 "last": all.primary_care_provider.provider[0].lname || "",
267 "first": all.primary_care_provider.provider[0].fname || ""
268 }
269 ],
270 "address": [
271 {
272 "street_lines": [
273 all.encounter_provider.facility_street
274 ],
275 "city": all.encounter_provider.facility_city,
276 "state": all.encounter_provider.facility_state,
277 "zip": all.encounter_provider.facility_postal_code,
278 "country": all.encounter_provider.facility_country_code
279 }
280 ],
281 "phone": [
282 {
283 "value": {
284 "number": all.encounter_provider.facility_phone || "",
286 }
287 }],
288 "organization": [
289 {
290 "identifiers": [
291 {
292 "identifier": "2.16.840.1.113883.19.5.9999.1393" //@todo need facility oid
293 }
294 ],
295 "name": [
296 all.encounter_provider.facility_name
297 ],
298 "address": [
299 {
300 "street_lines": [
301 all.encounter_provider.facility_street
302 ],
303 "city": all.encounter_provider.facility_city,
304 "state": all.encounter_provider.facility_state,
305 "zip": all.encounter_provider.facility_postal_code,
306 "country": all.encounter_provider.facility_country_code
307 }
308 ],
309 "phone": [
310 {
311 "number": all.encounter_provider.facility_phone,
312 "type": "primary work"
313 }
314 ]
315 }
316 ]
318 }
319 ]
322 }
323 }
325 function populateMedication(pd) {
326 pd.status = 'Completed'; //@todo invoke prescribed
327 return {
328 "date_time": {
329 "low": {
330 "date": fDate(pd.start_date),
331 "precision": "day"
332 },
333 /*"high": {
334 "date": pd.end_date ? fDate(pd.end_date) : "",
335 "precision": "day"
336 }*/
337 },
338 "identifiers": [{
339 "identifier": pd.sha_extension,
340 "extension": pd.extension || "UNK"
341 }],
342 "status": pd.status,
343 "sig": pd.direction,
344 "product": {
345 "identifiers": [{
346 "identifier": "2a620155-9d11-439e-92b3-5d9815ff4ee8",
347 "extension": "UNK"
348 }],
349 "unencoded_name": pd.drug,
350 "product": {
351 "name": pd.drug,
352 "code": pd.rxnorm,
353 /*"translations": [{
354 "name": pd.drug,
355 "code": pd.rxnorm,
356 "code_system_name": "RXNORM"
357 }],*/
358 "code_system_name": "RXNORM"
359 },
360 //"manufacturer": ""
361 },
362 "supply": {
363 "date_time": {
364 "low": {
365 "date": fDate(pd.start_date),
366 "precision": "day"
367 }
368 },
369 "repeatNumber": "0",
370 "quantity": "0",
371 "author": {
372 "date_time": {
373 "point": {
374 "date": fDate(pd.start_date),
375 "precision": getPrecision(fDate(pd.start_date))
376 }
377 },
378 "identifiers": [{
379 "identifier": "2.16.840.1.113883.4.6",
380 "extension": pd.npi || "UNK"
381 }],
382 "name": {
383 "prefix": pd.title,
384 "last": pd.lname,
385 "first": pd.fname
386 }
387 },
388 "instructions": {
389 "code": {
390 "name": "instruction",
391 "code": "409073007",
392 "code_system_name": "SNOMED CT"
393 },
394 "free_text": pd.instructions || "None Available"
395 },
396 },
397 "administration": {
398 "route": {
399 "name": pd.route || "",
400 "code": pd.route_code || "",
401 "code_system_name": "Medication Route FDA"
402 },
403 "form": {
404 "name": pd.form,
405 "code": pd.form_code,
406 "code_system_name": "Medication Route FDA"
407 },
408 "dose": {
409 "value": parseFloat(pd.size),
410 "unit": pd.unit,
411 },
412 /*"rate": {
413 "value": parseFloat(pd.dosage),
414 "unit": ""
415 },*/
416 "interval": {
417 "period": {
418 "value": parseFloat(pd.dosage),
419 "unit": pd.interval
420 },
421 "frequency": true
422 }
423 },
424 "performer": {
425 "identifiers": [{
426 "identifier": "2.16.840.1.113883.4.6",
427 "extension": pd.npi || "UNK"
428 }],
429 "organization": [{
430 "identifiers": [{
431 "identifier": pd.sha_extension,
432 "extension": pd.extension || "UNK"
433 }],
434 "name": [pd.performer_name]
435 }]
436 },
437 "drug_vehicle": {
438 "name": pd.form,
439 "code": pd.form_code,
440 "code_system_name": "RXNORM"
441 },
442 /*"precondition": {
443 "code": {
444 "code": "ASSERTION",
445 "code_system_name": "ActCode"
446 },
447 "value": {
448 "name": "none",
449 "code": "none",
450 "code_system_name": "SNOMED CT"
451 }
452 },
453 "indication": {
454 "identifiers": [{
455 "identifier": "db734647-fc99-424c-a864-7e3cda82e703",
456 "extension": "45665"
457 }],
458 "code": {
459 "name": "Finding",
460 "code": "404684003",
461 "code_system_name": "SNOMED CT"
462 },
463 "date_time": {
464 "low": {
465 "date": fDate(pd.start_date),
466 "precision": "day"
467 }
468 },
469 "value": {
470 "name": pd.indications,
471 "code": pd.indications_code,
472 "code_system_name": "SNOMED CT"
473 }
474 },*/
475 /*"dispense": {
476 "identifiers": [{
477 "identifier": "1.2.3.4.56789.1",
478 "extension": "cb734647-fc99-424c-a864-7e3cda82e704"
479 }],
480 "performer": {
481 "identifiers": [{
482 "identifier": "2.16.840.1.113883.19.5.9999.456",
483 "extension": "2981823"
484 }],
485 "address": [{
486 "street_lines": [pd.address],
487 "city": pd.city,
488 "state": pd.state,
489 "zip": pd.zip,
490 "country": "US"
491 }],
492 "organization": [{
493 "identifiers": [{
494 "identifier": "2.16.840.1.113883.19.5.9999.1393"
495 }],
496 "name": [pd.performer_name]
497 }]
498 },
499 "product": {
500 "identifiers": [{
501 "identifier": "2a620155-9d11-439e-92b3-5d9815ff4ee8"
502 }],
503 "unencoded_name": pd.drug,
504 "product": {
505 "name": pd.drug,
506 "code": pd.rxnorm,
507 "translations": [{
508 "name": pd.drug,
509 "code": pd.rxnorm,
510 "code_system_name": "RXNORM"
511 }],
512 "code_system_name": "RXNORM"
513 },
514 "manufacturer": ""
515 }
516 }*/
517 };
518 }
520 function populateEncounter(pd) {
521 return {
522 "encounter": {
523 "name": pd.visit_category ? pd.visit_category : '',
524 "code": pd.encounter_procedures ? pd.encounter_procedures.procedures.code : '',
525 "code_system_name": "CPT4",
526 "translations": [{
527 "name": "Ambulatory",
528 "code": "AMB",
529 "code_system_name": "ActCode"
530 }]
531 },
532 "identifiers": [{
533 "identifier": pd.sha_extension,
534 "extension": pd.extension
535 }],
536 "date_time": {
537 "point": {
538 "date": fDate(pd.date),
539 "precision": "second" //getPrecision(fDate(pd.date_formatted))
540 }
541 },
542 "performers": [{
543 "identifiers": [{
544 "identifier": "2.16.840.1.113883.4.6",
545 "extension": pd.npi || "UNK"
546 }],
547 "code": [{
548 "name": pd.physician_type,
549 "code": pd.physician_type_code,
550 "code_system_name": "SNOMED CT"
551 }],
552 "name": [
553 {
554 "last": pd.lname || "",
555 "first": pd.fname || ""
556 }
557 ],
558 "phone": [
559 {
560 "number": pd.work_phone,
561 "type": "work place"
562 }
563 ]
564 }],
565 "locations": [{
566 "name": pd.location,
567 "location_type": {
568 "name": pd.location_details,
569 "code": "1160-1",
570 "code_system_name": "HealthcareServiceLocation"
571 },
572 "address": [{
573 "street_lines": [pd.facility_address],
574 "city": pd.facility_city,
575 "state": pd.facility_state,
576 "zip": pd.facility_zip,
577 "country": pd.facility_country
578 }]
579 }],
580 "findings": [{
581 "identifiers": [{
582 "identifier": pd.sha_extension,
583 "extension": pd.extension
584 }],
585 "value": {
586 "name": pd.encounter_reason,
587 "code": "",
588 "code_system_name": "SNOMED CT"
589 },
590 "date_time": {
591 "low": {
592 "date": fDate(pd.date),
593 "precision": "day"
594 }
595 }
596 }]
597 };
598 }
600 function populateAllergy(pd) {
601 return {
602 "identifiers": [{
603 "identifier": "36e3e930-7b14-11db-9fe1-0800200c9a66",
604 "extension": pd.id || "UNK"
605 }],
606 "date_time": {
607 "point": {
608 "date": fDate(pd.startdate),
609 "precision": "day"
610 }
611 },
612 "observation": {
613 "identifiers": [{
614 "identifier": "4adc1020-7b14-11db-9fe1-0800200c9a66",
615 "extension": pd.extension || "UNK"
616 }],
617 "allergen": {
618 "name": pd.title,
619 "code": pd.rxnorm_code === 0 ? "" : pd.rxnorm_code,
620 "code_system_name": "RXNORM"
621 },
622 "intolerance": {
623 "name": "Propensity to adverse reactions to drug",
624 "code": pd.snomed_code || "420134006",
625 "code_system_name": "SNOMED CT"
626 },
627 "date_time": {
628 "low": {
629 "date": fDate(pd.startdate),
630 "precision": "day"
631 }
632 },
633 "status": {
634 "name": pd.allergy_status,
635 "code": pd.status_code === 0 ? "" : pd.status_code,
636 "code_system_name": "SNOMED CT"
637 },
638 "reactions": [{
639 "identifiers": [{
640 "identifier": "4adc1020-7b14-11db-9fe1-0800200c9a64"
641 }],
642 "date_time": {
643 "low": templateDate(pd.startdate, "day"),
644 "high": templateDate(pd.enddate, "day")
645 },
646 "reaction": {
647 "name": pd.reaction_text,
648 "code": pd.reaction_code === 0 ? "" : pd.reaction_code,
649 "code_system_name": "SNOMED CT"
650 },
651 "severity": {
652 "code": {
653 "name": pd.outcome,
654 "code": pd.outcome_code === 0 ? "" : pd.outcome_code,
655 "code_system_name": "SNOMED CT"
656 },
657 /*"interpretation": {
658 "name": "",
659 "code": "",
660 "code_system_name": "Observation Interpretation"
661 }*/
662 }
663 }],
664 "severity": {
665 "code": {
666 "name": pd.outcome,
667 "code": pd.outcome_code === 0 ? "" : pd.outcome_code,
668 "code_system_name": "SNOMED CT"
669 },
670 /*"interpretation": {
671 "name": "UNK",
672 "code": "",
673 "code_system_name": "Observation Interpretation"
674 }*/
675 }
676 }
677 };
678 }
680 function populateProblem(pd) {
681 return {
682 "date_time": {
683 "low": {
684 "date": fDate(pd.start_date_table),
685 "precision": "day"
686 },
687 /*"high": {
688 "date": fDate(pd.end_date),
689 "precision": "day"
690 }*/
691 },
692 "identifiers": [{
693 "identifier": pd.sha_extension,
694 "extension": pd.extension || "UNK"
695 }],
696 "problem": {
697 "code": {
698 "name": trim(pd.title),
699 "code": cleanCode(pd.code),
700 "code_system_name": "ICD10"
701 },
702 "date_time": {
703 "low": {
704 "date": fDate(pd.start_date),
705 "precision": "day"
706 },
707 /*"high": {
708 "date": fDate(pd.end_date),
709 "precision": getPrecision()
710 }*/
711 }
712 },
713 "performer": [
714 {
715 "identifiers": [
716 {
717 "identifier": "2.16.840.1.113883.4.6",
718 "extension": all.primary_care_provider.provider[0].npi || "UNK"
719 }
720 ],
721 "name": [
722 {
723 "last": all.primary_care_provider.provider[0].lname || "",
724 "first": all.primary_care_provider.provider[0].fname || ""
725 }
726 ]
727 }],
728 "onset_age": pd.age,
729 "onset_age_unit": "Year",
730 "status": {
731 "name": pd.status,
732 "date_time": {
733 "low": {
734 "date": fDate(pd.start_date),
735 "precision": "day"
736 },
737 /*"high": {
738 "date": fDate(pd.end_date),
739 "precision": getPrecision()
740 }*/
741 }
742 },
743 "patient_status": pd.observation,
744 "source_list_identifiers": [{
745 "identifier": pd.sha_extension,
746 "extension": pd.extension || "UNK"
747 }]
748 };
750 }
752 function populateProcedure(pd) {
753 return {
754 "procedure": {
755 "name": pd.description,
756 "code": pd.code,
757 "code_system_name": "CPT4"
758 },
759 "identifiers": [{
760 "identifier": "d68b7e32-7810-4f5b-9cc2-acd54b0fd85d",
761 "extension": pd.extension
762 }],
763 "status": "completed",
764 "date_time": {
765 "point": {
766 "date": fDate(pd.date),
767 "precision": "day"
768 }
769 },
770 /*"body_sites": [{
771 "name": "",
772 "code": "",
773 "code_system_name": ""
774 }],
775 "specimen": {
776 "identifiers": [{
777 "identifier": "c2ee9ee9-ae31-4628-a919-fec1cbb58683"
778 }],
779 "code": {
780 "name": "",
781 "code": "",
782 "code_system_name": "SNOMED CT"
783 }
784 },*/
785 "performers": [{
786 "identifiers": [{
787 "identifier": "2.16.840.1.113883.4.6",
788 "extension": pd.npi || "UNK"
789 }],
790 "address": [{
791 "street_lines": [pd.address],
792 "city": pd.city,
793 "state": pd.state,
794 "zip": pd.zip,
795 "country": ""
796 }],
797 "phone": [{
798 "number": pd.work_phone,
799 "type": "work place"
800 }],
801 "organization": [{
802 "identifiers": [{
803 "identifier": pd.facility_sha_extension,
804 "extension": pd.facility_extension
805 }],
806 "name": [pd.facility_name],
807 "address": [{
808 "street_lines": [pd.facility_address],
809 "city": pd.facility_city,
810 "state": pd.facility_state,
811 "zip": pd.facility_zip,
812 "country": pd.facility_country
813 }],
814 "phone": [{
815 "number": pd.facility_phone,
816 "type": "work place"
817 }]
818 }]
819 }],
820 "procedure_type": "procedure"
821 };
822 }
824 function populateResult(pd) {
825 let icode = pd.subtest.abnormal_flag;
826 switch (pd.subtest.abnormal_flag.toUpperCase()) {
827 case "NO":
828 icode = "Normal";
829 break;
830 case "YES":
831 icode = "Abnormal";
832 break;
833 case "":
834 icode = "UNK";
835 break;
836 }
837 return {
838 "identifiers": [{
839 "identifier": pd.subtest.root,
840 "extension": pd.subtest.extension
841 }],
842 "result": {
843 "name": pd.title,
844 "code": pd.subtest.result_code || "",
845 "code_system_name": "LOINC"
846 },
847 "date_time": {
848 "point": {
849 "date": fDate(pd.date_ordered),
850 "precision": "day"
851 }
852 },
853 "status": pd.order_status,
854 "reference_range": {
855 "range": pd.subtest.range //OpenEMR doesn't have high/low so show range as text.
856 },
857 /*"reference_range": {
858 "low": pd.subtest.range,
859 "high": pd.subtest.range,
860 "unit": pd.subtest.unit
861 },*/
862 "interpretations": [icode],
863 "value": parseFloat(pd.subtest.result_value) || pd.subtest.result_value || "",
864 "unit": pd.subtest.unit
865 };
866 }
868 function getResultSet(results) {
870 if (!results) return '';
872 let tResult = results.result[0] || results.result;
873 var resultSet = {
874 "identifiers": [{
875 "identifier": tResult.root,
876 "extension": tResult.extension
877 }],
878 "author": [
879 {
880 "date_time": {
881 "point": {
882 "date": fDate(tResult.date_ordered),
883 "precision": getPrecision(fDate(tResult.date_ordered))
884 }
885 },
886 "identifiers": [
887 {
888 "identifier": "2.16.840.1.113883.4.6",
889 "extension": all.primary_care_provider.provider.npi || "UNK"
890 }
891 ],
892 "name": [
893 {
894 "last": all.primary_care_provider.provider.lname || "",
895 "first": all.primary_care_provider.provider.fname || ""
896 }
897 ]
898 }],
899 "result_set": {
900 "name": tResult.test_name,
901 "code": tResult.test_code,
902 "code_system_name": "LOINC"
903 }
904 };
905 var rs = [];
906 var many = [];
907 var theone = {};
908 var count = 0;
909 many.results = [];
910 try {
911 count = isOne(results.result);
912 } catch (e) {
913 count = 0;
914 }
915 if (count > 1) {
916 for (let i in results.result) {
917 theone[i] = populateResult(results.result[i]);
918 many.results.push(theone[i]);
919 }
920 } else if (count !== 0) {
921 theone = populateResult(results.result);
922 many.results.push(theone);
923 }
924 rs.results = Object.assign(resultSet);
925 rs.results.results = Object.assign(many.results);
926 return rs;
927 }
929 function getPlanOfCare(pd) {
930 return {
931 "plan": {
932 "name": pd.code_text,
933 "code": pd.code,
934 "code_system_name": "SNOMED CT"
935 },
936 "identifiers": [{
937 "identifier": "9a6d1bac-17d3-4195-89a4-1121bc809b4a"
938 }],
939 "date_time": {
940 "center": {
941 "date": fDate(pd.date),
942 "precision": "day"
943 }
944 },
945 "type": "observation",
946 "status": {
947 "code": pd.status
948 },
949 "subType": pd.description
950 };
951 }
953 function populateVital(pd) {
954 return [{
955 "identifiers": [{
956 "identifier": "2.16.840.1.113883.3.140.1.0.6.10.14.1",
957 "extension": pd.extension_bps
958 }],
959 "vital": {
960 "name": "Blood Pressure Systolic",
961 "code": "8480-6",
962 "code_system_name": "LOINC"
963 },
964 "status": "completed",
965 "date_time": {
966 "point": {
967 "date": fDate(pd.effectivetime),
968 "precision": getPrecision(fDate(pd.effectivetime))
969 }
970 },
971 "value": parseFloat(pd.bps),
972 "unit": "mm[Hg]"
973 }, {
974 "identifiers": [{
975 "identifier": "2.16.840.1.113883.3.140.1.0.6.10.14.1",
976 "extension": pd.extension_bpd
977 }],
978 "vital": {
979 "name": "Blood Pressure Diastolic",
980 "code": "8462-4",
981 "code_system_name": "LOINC"
982 },
983 "status": "completed",
984 "date_time": {
985 "point": {
986 "date": fDate(pd.effectivetime),
987 "precision": getPrecision(fDate(pd.effectivetime))
988 }
989 },
990 "interpretations": ["Normal"],
991 "value": parseFloat(pd.bpd),
992 "unit": "mm[Hg]"
993 }, {
994 "identifiers": [{
995 "identifier": "2.16.840.1.113883.3.140.1.0.6.10.14.1",
996 "extension": pd.extension_pulse
997 }],
998 "vital": {
999 "name": "Heart Rate",
1000 "code": "8867-4",
1001 "code_system_name": "LOINC"
1002 },
1003 "status": "completed",
1004 "date_time": {
1005 "point": {
1006 "date": fDate(pd.effectivetime),
1007 "precision": getPrecision(fDate(pd.effectivetime))
1008 }
1009 },
1010 "interpretations": ["Normal"],
1011 "value": parseFloat(pd.pulse),
1012 "unit": "/min"
1013 }, {
1014 "identifiers": [{
1015 "identifier": "2.16.840.1.113883.3.140.1.0.6.10.14.1",
1016 "extension": pd.extension_breath
1017 }],
1018 "vital": {
1019 "name": "Respiratory Rate",
1020 "code": "9279-1",
1021 "code_system_name": "LOINC"
1022 },
1023 "status": "completed",
1024 "date_time": {
1025 "point": {
1026 "date": fDate(pd.effectivetime),
1027 "precision": getPrecision(fDate(pd.effectivetime))
1028 }
1029 },
1030 "interpretations": ["Normal"],
1031 "value": parseFloat(pd.breath),
1032 "unit": "/min"
1033 }, {
1034 "identifiers": [{
1035 "identifier": "2.16.840.1.113883.3.140.1.0.6.10.14.1",
1036 "extension": pd.extension_temperature
1037 }],
1038 "vital": {
1039 "name": "Body Temperature",
1040 "code": "8310-5",
1041 "code_system_name": "LOINC"
1042 },
1043 "status": "completed",
1044 "date_time": {
1045 "point": {
1046 "date": fDate(pd.effectivetime),
1047 "precision": getPrecision(fDate(pd.effectivetime))
1048 }
1049 },
1050 "interpretations": ["Normal"],
1051 "value": parseFloat(pd.temperature),
1052 "unit": "degF"
1053 }, {
1054 "identifiers": [{
1055 "identifier": "2.16.840.1.113883.3.140.1.0.6.10.14.1",
1056 "extension": pd.extension_height
1057 }],
1058 "vital": {
1059 "name": "Height",
1060 "code": "8302-2",
1061 "code_system_name": "LOINC"
1062 },
1063 "status": "completed",
1064 "date_time": {
1065 "point": {
1066 "date": fDate(pd.effectivetime),
1067 "precision": getPrecision(fDate(pd.effectivetime))
1068 }
1069 },
1070 "interpretations": ["Normal"],
1071 "value": parseFloat(pd.height),
1072 "unit": pd.unit_height
1073 }, {
1074 "identifiers": [{
1075 "identifier": "2.16.840.1.113883.3.140.1.0.6.10.14.1",
1076 "extension": pd.extension_weight
1077 }],
1078 "vital": {
1079 "name": "Weight Measured",
1080 "code": "3141-9",
1081 "code_system_name": "LOINC"
1082 },
1083 "status": "completed",
1084 "date_time": {
1085 "point": {
1086 "date": fDate(pd.effectivetime),
1087 "precision": getPrecision(fDate(pd.effectivetime))
1088 }
1089 },
1090 "interpretations": ["Normal"],
1091 "value": parseFloat(pd.weight),
1092 "unit": pd.unit_weight
1093 }, {
1094 "identifiers": [{
1095 "identifier": "2.16.840.1.113883.3.140.1.0.6.10.14.1",
1096 "extension": pd.extension_BMI
1097 }],
1098 "vital": {
1099 "name": "BMI (Body Mass Index)",
1100 "code": "39156-5",
1101 "code_system_name": "LOINC"
1102 },
1103 "status": "completed",
1104 "date_time": {
1105 "point": {
1106 "date": fDate(pd.effectivetime),
1107 "precision": getPrecision(fDate(pd.effectivetime))
1108 }
1109 },
1110 "interpretations": ["Normal"],
1111 "value": parseFloat(pd.BMI),
1112 "unit": "kg/m2"
1113 }];
1114 }
1116 function populateSocialHistory(pd) {
1117 return {
1118 "date_time": {
1119 "low": templateDate(pd.date, "day")
1120 //"high": templateDate(pd.date, "day")
1121 },
1122 "identifiers": [{
1123 "identifier": pd.sha_extension,
1124 "extension": pd.extension
1125 }],
1126 "code": {
1127 "name": pd.element
1128 },
1129 "value": pd.description
1130 };
1131 }
1133 function populateImmunization(pd) {
1134 return {
1135 "date_time": {
1136 "point": {
1137 "date": fDate(pd.administered_on),
1138 "precision": "month"
1139 }
1140 },
1141 "identifiers": [{
1142 "identifier": "e6f1ba43-c0ed-4b9b-9f12-f435d8ad8f92",
1143 "extension": pd.extension || "UNK"
1144 }],
1145 "status": "complete",
1146 "product": {
1147 "product": {
1148 "name": pd.code_text,
1149 "code": pd.cvx_code,
1150 "code_system_name": "CVX"
1151 /*"translations": [{
1152 "name": "",
1153 "code": "",
1154 "code_system_name": "CVX"
1155 }]*/
1156 },
1157 "lot_number": "1",
1158 "manufacturer": "UNK"
1159 },
1160 "administration": {
1161 "route": {
1162 "name": pd.route_of_administration,
1163 "code": pd.route_code,
1164 "code_system_name": "Medication Route FDA"
1165 },
1166 "dose": {
1167 "value": 50,
1168 "unit": "mcg"
1169 }
1170 },
1171 "performer": {
1172 "identifiers": [{
1173 "identifier": "2.16.840.1.113883.4.6",
1174 "extension": npiProvider
1175 }],
1176 "name": [{
1177 "last": pd.lname,
1178 "first": pd.fname
1179 }],
1180 "address": [{
1181 "street_lines": [pd.address],
1182 "city": pd.city,
1183 "state": pd.state,
1184 "zip": pd.zip,
1185 "country": "US"
1186 }],
1187 "organization": [{
1188 "identifiers": [{
1189 "identifier": "2.16.840.1.113883.4.6",
1190 "extension": npiFacility
1191 }],
1192 "name": [pd.facility_name]
1193 }]
1194 },
1195 "instructions": {
1196 "code": {
1197 "name": "immunization education",
1198 "code": "171044003",
1199 "code_system_name": "SNOMED CT"
1200 },
1201 "free_text": "Needs Attention for more data."
1202 }
1203 };
1204 }
1206 function populatePayer(pd) {
1207 return {
1208 "identifiers": [{
1209 "identifier": "1fe2cdd0-7aad-11db-9fe1-0800200c9a66"
1210 }],
1211 "policy": {
1212 "identifiers": [{
1213 "identifier": "3e676a50-7aac-11db-9fe1-0800200c9a66"
1214 }],
1215 "code": {
1216 "code": "SELF",
1217 "code_system_name": "HL7 RoleCode"
1218 },
1219 "insurance": {
1220 "code": {
1221 "code": "PAYOR",
1222 "code_system_name": "HL7 RoleCode"
1223 },
1224 "performer": {
1225 "identifiers": [{
1226 "identifier": "2.16.840.1.113883.19"
1227 }],
1228 "address": [{
1229 "street_lines": ["123 Insurance Road"],
1230 "city": "Blue Bell",
1231 "state": "MA",
1232 "zip": "02368",
1233 "country": "US",
1234 "use": "work place"
1235 }],
1236 "phone": [{
1237 "number": "(781)555-1515",
1238 "type": "work place"
1239 }],
1240 "organization": [{
1241 "name": ["Good Health Insurance"],
1242 "address": [{
1243 "street_lines": ["123 Insurance Road"],
1244 "city": "Blue Bell",
1245 "state": "MA",
1246 "zip": "02368",
1247 "country": "US",
1248 "use": "work place"
1249 }],
1250 "phone": [{
1251 "number": "(781)555-1515",
1252 "type": "work place"
1253 }]
1254 }],
1255 "code": [{
1256 "code": "PAYOR",
1257 "code_system_name": "HL7 RoleCode"
1258 }]
1259 }
1260 }
1261 },
1262 "guarantor": {
1263 "code": {
1264 "code": "GUAR",
1265 "code_system_name": "HL7 Role"
1266 },
1267 "identifiers": [{
1268 "identifier": "329fcdf0-7ab3-11db-9fe1-0800200c9a66"
1269 }],
1270 "name": [{
1271 "prefix": "Mr.",
1272 "middle": ["Frankie"],
1273 "last": "Everyman",
1274 "first": "Adam"
1275 }],
1276 "address": [{
1277 "street_lines": ["17 Daws Rd."],
1278 "city": "Blue Bell",
1279 "state": "MA",
1280 "zip": "02368",
1281 "country": "US",
1282 "use": "primary home"
1283 }],
1284 "phone": [{
1285 "number": "(781)555-1212",
1286 "type": "primary home"
1287 }]
1288 },
1289 "participant": {
1290 "code": {
1291 "name": "Self",
1292 "code": "SELF",
1293 "code_system_name": "HL7 Role"
1294 },
1295 "performer": {
1296 "identifiers": [{
1297 "identifier": "14d4a520-7aae-11db-9fe1-0800200c9a66",
1298 "extension": "1138345"
1299 }],
1300 "address": [{
1301 "street_lines": ["17 Daws Rd."],
1302 "city": "Blue Bell",
1303 "state": "MA",
1304 "zip": "02368",
1305 "country": "US",
1306 "use": "primary home"
1307 }],
1308 "code": [{
1309 "name": "Self",
1310 "code": "SELF",
1311 "code_system_name": "HL7 Role"
1312 }]
1313 },
1314 "name": [{
1315 "prefix": "Mr.",
1316 "middle": ["A."],
1317 "last": "Everyman",
1318 "first": "Frank"
1319 }]
1320 },
1321 "policy_holder": {
1322 "performer": {
1323 "identifiers": [{
1324 "identifier": "2.16.840.1.113883.19",
1325 "extension": "1138345"
1326 }],
1327 "address": [{
1328 "street_lines": ["17 Daws Rd."],
1329 "city": "Blue Bell",
1330 "state": "MA",
1331 "zip": "02368",
1332 "country": "US",
1333 "use": "primary home"
1334 }]
1335 }
1336 },
1337 "authorization": {
1338 "identifiers": [{
1339 "identifier": "f4dce790-8328-11db-9fe1-0800200c9a66"
1340 }],
1341 "procedure": {
1342 "code": {
1343 "name": "Colonoscopy",
1344 "code": "73761001",
1345 "code_system_name": "SNOMED CT"
1346 }
1347 }
1348 }
1349 };
1350 }
1352 function populateHeader(pd) {
1353 var head = {
1354 "identifiers": [
1355 {
1356 "identifier": oidFacility,
1357 "extension": "TT988"
1358 }
1359 ],
1360 "code": {
1361 "name": "Continuity of Care Document",
1362 "code": "34133-9",
1363 "code_system_name": "LOINC"
1364 },
1365 "template": [
1366 "2.16.840.1.113883.10.20.22.1.1",
1367 "2.16.840.1.113883.10.20.22.1.2"
1368 ],
1369 "title": "Clinical Health Summary",
1370 "date_time": {
1371 "point": {
1372 "date": fDate(pd.created_time) || "",
1373 "precision": getPrecision(fDate(pd.created_time))
1374 }
1375 },
1376 "author": {
1377 "author": [
1378 {
1379 "identifiers": [
1380 {
1381 "identifier": "2.16.840.1.113883.4.6",
1382 "extension": pd.author.npi || "UNK"
1383 }
1384 ],
1385 "name": [
1386 {
1387 "last": pd.author.lname,
1388 "first": pd.author.fname
1389 }
1390 ],
1391 "address": [
1392 {
1393 "street_lines": [
1394 pd.author.streetAddressLine
1395 ],
1396 "city": pd.author.city,
1397 "state": pd.author.state,
1398 "zip": pd.author.postalCode,
1399 "country": pd.author.country
1400 }
1401 ],
1402 "phone": [
1403 {
1404 "number": pd.author.telecom,
1405 "use": "work place"
1406 }
1407 ],
1408 "code": [
1409 {
1410 "name": "UNK",
1411 "code": ""
1412 }
1413 ],
1414 "organization": [
1415 {
1416 "identity": [
1417 {
1418 "root": "2.16.840.1.113883.4.6",
1419 "extension": npiFacility || "UNK"
1420 }
1421 ],
1422 "name": [
1423 pd.encounter_provider.facility_name
1424 ],
1425 "address": [
1426 {
1427 "street_lines": [
1428 pd.encounter_provider.facility_street
1429 ],
1430 "city": pd.encounter_provider.facility_city,
1431 "state": pd.encounter_provider.facility_state,
1432 "zip": pd.encounter_provider.facility_postal_code,
1433 "country": pd.encounter_provider.facility_country_code
1434 }
1435 ],
1436 "phone": [
1437 {
1438 "number": pd.encounter_provider.facility_phone,
1439 "type": "work primary"
1440 }
1441 ]
1442 }
1443 ]
1444 }
1445 ]
1446 },
1447 "custodian": {
1448 "identity": [
1449 {
1450 "root": "2.16.840.1.113883.4.6",
1451 "extension": npiFacility || "UNK"
1452 }
1453 ],
1454 "name": [
1455 pd.encounter_provider.facility_name
1456 ],
1457 "address": [
1458 {
1459 "street_lines": [
1460 pd.encounter_provider.facility_street
1461 ],
1462 "city": pd.encounter_provider.facility_city,
1463 "state": pd.encounter_provider.facility_state,
1464 "zip": pd.encounter_provider.facility_postal_code,
1465 "country": pd.encounter_provider.facility_country_code
1466 }
1467 ],
1468 "phone": [
1469 {
1470 "number": pd.encounter_provider.facility_phone,
1471 "type": "work primary"
1472 }
1473 ]
1474 },
1475 /*"data_enterer": {
1476 "identifiers": [
1477 {
1478 "identifier": "2.16.840.1.113883.4.6",
1479 "extension": "999999943252"
1480 }
1481 ],
1482 "name": [
1483 {
1484 "last": pd.data_enterer.lname,
1485 "first": pd.data_enterer.fname
1486 }
1487 ],
1488 "address": [
1489 {
1490 "street_lines": [
1491 pd.data_enterer.streetAddressLine
1492 ],
1493 "city": pd.data_enterer.city,
1494 "state": pd.data_enterer.state,
1495 "zip": pd.data_enterer.postalCode,
1496 "country": pd.data_enterer.country
1497 }
1498 ],
1499 "phone": [
1500 {
1501 "number": pd.data_enterer.telecom,
1502 "type": "work place"
1503 }
1504 ]
1505 },
1506 "informant": {
1507 "identifiers": [
1508 {
1509 "identifier": "2.16.840.1.113883.19.5",
1510 "extension": "KP00017"
1511 }
1512 ],
1513 "name": [
1514 {
1515 "last": pd.informer.lname || "",
1516 "first": pd.informer.fname || ""
1517 }
1518 ],
1519 "address": [
1520 {
1521 "street_lines": [
1522 pd.informer.streetAddressLine || ""
1523 ],
1524 "city": pd.informer.city,
1525 "state": pd.informer.state,
1526 "zip": pd.informer.postalCode,
1527 "country": pd.informer.country
1528 }
1529 ],
1530 "phone": [
1531 {
1532 "number": pd.informer.telecom || "",
1533 "type": "work place"
1534 }
1535 ]
1536 },*/
1537 "service_event": { // @todo maybe move this to attributed or write z-schema template
1538 "code": {
1539 "name": "",
1540 "code": "",
1541 "code_system_name": "SNOMED CT"
1542 },
1543 "date_time": {
1544 "low": {
1545 "date": "",
1546 "precision": getPrecision()
1547 },
1548 "high": {
1549 "date": pd.created_time,
1550 "precision": getPrecision()
1551 }
1552 },
1553 "performer": [
1554 {
1555 "performer": [
1556 {
1557 "identifiers": [
1558 {
1559 "identifier": "2.16.840.1.113883.4.6",
1560 "extension": "PseudoMD-1"
1561 }
1562 ],
1563 "name": [
1564 {
1565 "last": pd.information_recipient.lname,
1566 "first": pd.information_recipient.fname
1567 }
1568 ],
1569 "address": [
1570 {
1571 "street_lines": [
1572 pd.information_recipient.streetAddressLine
1573 ],
1574 "city": pd.information_recipient.city,
1575 "state": pd.information_recipient.state,
1576 "zip": pd.information_recipient.postalCode,
1577 "country": pd.information_recipient.country
1578 }
1579 ],
1580 "phone": [
1581 {
1582 "number": pd.information_recipient.telecom,
1583 "type": "work place"
1584 }
1585 ],
1586 "organization": [
1587 {
1588 "identifiers": [
1589 {
1590 "identifier": "2.16.840.1.113883.19.5.9999.1393"
1591 }
1592 ],
1593 "name": [
1594 pd.encounter_provider.facility_name
1595 ],
1596 "address": [
1597 {
1598 "street_lines": [
1599 pd.encounter_provider.facility_street
1600 ],
1601 "city": pd.encounter_provider.facility_city,
1602 "state": pd.encounter_provider.facility_state,
1603 "zip": pd.encounter_provider.facility_postal_code,
1604 "country": pd.encounter_provider.facility_country_code
1605 }
1606 ],
1607 "phone": [
1608 {
1609 "number": pd.encounter_provider.facility_phone,
1610 "type": "primary work"
1611 }
1612 ]
1613 }
1614 ],
1615 "code": [
1616 {
1617 "name": "UNK",
1618 "code": "",
1619 "code_system_name": "Provider Codes"
1620 }
1621 ]
1622 }
1623 ],
1624 "code": {
1625 "name": "Primary Performer",
1626 "code": "PP",
1627 "code_system_name": "Provider Role"
1628 }
1629 }
1630 ]
1631 }
1632 };
1633 return head;
1634 }
1636 function getMeta(pd) {
1637 var meta = {};
1638 meta = {
1639 "type": "CCDA",
1640 "identifiers": [
1641 {
1642 "identifier": "2.16.840.1.113883.19.5.99999.1",
1643 "extension": "TT988"
1644 }
1645 ],
1646 "confidentiality": "Normal",
1647 "set_id": {
1648 "identifier": "2.16.840.1.113883.19.5.99999.19",
1649 "extension": "sTT988"
1650 }
1651 }
1652 return meta;
1653 }
1655 function genCcda(pd) {
1656 var doc = {};
1657 var data = {};
1658 var count = 0;
1659 var many = [];
1660 var theone = {};
1662 all = pd;
1663 npiProvider = all.primary_care_provider.provider[0].npi;
1664 oidFacility = all.encounter_provider.facility_oid;
1665 npiFacility = all.encounter_provider.facility_npi;
1667 // Demographics
1668 let demographic = populateDemographic(pd.patient, pd.guardian, pd);
1669 Object.assign(demographic, populateProviders());
1670 data.demographics = Object.assign(demographic);
1672 // vitals
1673 many.vitals = [];
1674 try {
1675 count = isOne(pd.history_physical.vitals_list.vitals);
1676 } catch (e) {
1677 count = 0
1678 }
1679 if (count > 1) {
1680 for (let i in pd.history_physical.vitals_list.vitals) {
1681 theone = populateVital(pd.history_physical.vitals_list.vitals[i]);
1682 many.vitals.push.apply(many.vitals, theone);
1683 }
1684 } else if (count === 1) {
1685 theone = populateVital(pd.history_physical.vitals_list.vitals);
1686 many.vitals.push(theone);
1687 }
1688 data.vitals = Object.assign(many.vitals);
1689 // Medications
1690 let meds = [];
1691 let m = {};
1692 meds.medications = [];
1693 try {
1694 count = isOne(pd.medications.medication);
1695 } catch (e) {
1696 count = 0
1697 }
1698 if (count > 1) {
1699 for (let i in pd.medications.medication) {
1700 m[i] = populateMedication(pd.medications.medication[i]);
1701 meds.medications.push(m[i]);
1702 }
1703 } else if (count !== 0) {
1704 m = populateMedication(pd.medications.medication);
1705 meds.medications.push(m);
1706 }
1707 data.medications = Object.assign(meds.medications);
1708 // Encounters
1709 let encs = [];
1710 let enc = {};
1711 encs.encounters = [];
1712 try {
1713 count = isOne(pd.encounter_list.encounter);
1714 } catch (e) {
1715 count = 0
1716 }
1717 if (count > 1) {
1718 for (let i in pd.encounter_list.encounter) {
1719 enc[i] = populateEncounter(pd.encounter_list.encounter[i]);
1720 encs.encounters.push(enc[i]);
1721 }
1722 } else if (count !== 0) {
1723 enc = populateEncounter(pd.encounter_list.encounter);
1724 encs.encounters.push(enc);
1725 }
1726 data.encounters = Object.assign(encs.encounters);
1728 // Allergies
1729 let allergies = [];
1730 let allergy = {};
1731 allergies.allergies = [];
1732 try {
1733 count = isOne(pd.allergies.allergy);
1734 } catch (e) {
1735 count = 0
1736 }
1737 if (count > 1) {
1738 for (let i in pd.allergies.allergy) {
1739 allergy[i] = populateAllergy(pd.allergies.allergy[i]);
1740 allergies.allergies.push(allergy[i]);
1741 }
1742 } else if (count !== 0) {
1743 allergy = populateAllergy(pd.allergies.allergy);
1744 allergies.allergies.push(allergy);
1745 }
1746 data.allergies = Object.assign(allergies.allergies);
1748 // Problems
1749 let problems = [];
1750 let problem = {};
1751 problems.problems = [];
1752 try {
1753 count = isOne(pd.problem_lists.problem);
1754 } catch (e) {
1755 count = 0
1756 }
1757 if (count > 1) {
1758 for (let i in pd.problem_lists.problem) {
1759 problem[i] = populateProblem(pd.problem_lists.problem[i], pd);
1760 problems.problems.push(problem[i]);
1761 }
1762 } else if (count !== 0) {
1763 problem = populateProblem(pd.problem_lists.problem);
1764 problems.problems.push(problem);
1765 }
1766 data.problems = Object.assign(problems.problems);
1767 // Procedures
1768 many = [];
1769 theone = {};
1770 many.procedures = [];
1771 try {
1772 count = isOne(pd.procedures.procedure);
1773 } catch (e) {
1774 count = 0
1775 }
1776 if (count > 1) {
1777 for (let i in pd.procedures.procedure) {
1778 theone[i] = populateProcedure(pd.procedures.procedure[i]);
1779 many.procedures.push(theone[i]);
1780 }
1781 } else if (count !== 0) {
1782 theone = populateProcedure(pd.procedures.procedure);
1783 many.procedures.push(theone);
1784 }
1786 data.procedures = Object.assign(many.procedures);
1787 // Results
1788 if (pd.results)
1789 data.results = Object.assign(getResultSet(pd.results, pd)['results']);
1791 // Immunizations
1792 many = [];
1793 theone = {};
1794 many.immunizations = [];
1795 try {
1796 count = isOne(pd.immunizations.immunization);
1797 } catch (e) {
1798 count = 0;
1799 }
1800 if (count > 1) {
1801 for (let i in pd.immunizations.immunization) {
1802 theone[i] = populateImmunization(pd.immunizations.immunization[i]);
1803 many.immunizations.push(theone[i]);
1804 }
1805 } else if (count !== 0) {
1806 theone = populateImmunization(pd.immunizations.immunization);
1807 many.immunizations.push(theone);
1808 }
1809 data.immunizations = Object.assign(many.immunizations);
1810 // Plan of Care
1811 many = [];
1812 theone = {};
1813 many.plan_of_care = [];
1814 try {
1815 count = isOne(pd.planofcare); // ccm doesn't send array of items
1816 } catch (e) {
1817 count = 0
1818 }
1819 if (count > 1) {
1820 for (let i in pd.planofcare.item) {
1821 theone[i] = getPlanOfCare(pd.planofcare.item[i]);
1822 many.plan_of_care.push(theone[i]);
1823 }
1824 } else if (count !== 0) {
1825 theone = getPlanOfCare(pd.planofcare.item);
1826 many.plan_of_care.push(theone);
1827 }
1829 data.plan_of_care = Object.assign(many.plan_of_care);
1830 // Social History
1831 many = [];
1832 theone = {};
1833 many.social_history = [];
1834 try {
1835 count = isOne(pd.history_physical.social_history.history_element);
1836 } catch (e) {
1837 count = 0
1838 }
1839 if (count > 1) {
1840 for (let i in pd.history_physical.social_history.history_element) {
1841 if (i > 0) break;
1842 theone[i] = populateSocialHistory(pd.history_physical.social_history.history_element[i]);
1843 many.social_history.push(theone[i]);
1844 }
1845 } else if (count !== 0) {
1846 theone = populateSocialHistory(pd.history_physical.social_history.history_element);
1847 many.social_history.push(theone);
1848 }
1850 data.social_history = Object.assign(many.social_history);
1852 // ------------------------------------------ End Sections ----------------------------------------//
1854 doc.data = Object.assign(data);
1855 let meta = getMeta(pd);
1856 let header = populateHeader(pd);
1858 meta.ccda_header = Object.assign(header);
1859 doc.meta = Object.assign(meta);
1860 let xml = bbg.generateCCD(doc);
1862 // Debug
1863 /*fs.writeFile("bbtest.json", JSON.stringify(doc, null, 4), function (err) {
1864 if (err) {
1865 return console.log(err);
1866 }
1867 console.log("Json saved!");
1868 });
1869 fs.writeFile("bbtest.xml", xml, function (err) {
1870 if (err) {
1871 return console.log(err);
1872 }
1873 console.log("Xml saved!");
1874 });*/
1876 return xml;
1877 }
1879 function processConnection(connection) {
1880 conn = connection; // make it global
1881 var remoteAddress = conn.remoteAddress + ':' + conn.remotePort;
1882 //console.log(remoteAddress);
1883 conn.setEncoding('utf8');
1885 // patched out re: buffer overrun fix. maintain for history.
1886 /*function eventData(xml) {
1887 xml = xml.replace(/(\u000b|\u001c)/gm, "").trim();
1888 // Sanity check from service manager
1889 if (xml === 'status' || xml.length < 80) {
1890 conn.write("statusok" + String.fromCharCode(28) + "\r\r");
1891 conn.end('');
1892 return;
1893 }
1895 // ---------------------start--------------------------------
1896 let doc = "";
1897 xml = xml.toString().replace(/\t\s+/g, ' ').trim();
1899 to_json(xml, function (error, data) {
1900 // console.log(JSON.stringify(data, null, 4));
1901 if (error) { // need try catch
1902 console.log('toJson error: ' + error + 'Len: ' + xml.length);
1903 return;
1904 }
1905 doc = genCcda(data.CCDA);
1906 });
1908 doc = headReplace(doc);
1909 doc = doc.toString().replace(/(\u000b|\u001c|\r)/gm, "").trim();
1910 //console.log(doc);
1911 let chunk = "";
1912 let numChunks = Math.ceil(doc.length / 1024);
1913 for (let i = 0, o = 0; i < numChunks; ++i, o += 1024) {
1914 chunk = doc.substr(o, 1024);
1915 conn.write(chunk);
1916 }
1918 conn.write(String.fromCharCode(28) + "\r\r" + '');
1919 conn.end();
1921 }*/
1923 var xml_complete = "";
1925 function eventData(xml) {
1926 xml = xml.replace(/(\u000b|\u001c)/gm, "").trim();
1927 // Sanity check from service manager
1928 if (xml === 'status' || xml.length < 80) {
1929 conn.write("statusok" + String.fromCharCode(28) + "\r\r");
1930 conn.end('');
1931 return;
1932 }
1933 xml_complete += xml.toString();
1934 if (xml.toString().match(/\<\/CCDA\>$/g)) {
1935 // ---------------------start--------------------------------
1936 let doc = "";
1937 xml_complete = xml_complete.replace(/\t\s+/g, ' ').trim();
1939 to_json(xml_complete, function (error, data) {
1940 // console.log(JSON.stringify(data, null, 4));
1941 if (error) { // need try catch
1942 console.log('toJson error: ' + error + 'Len: ' + xml_complete.length);
1943 return;
1944 }
1945 doc = genCcda(data.CCDA);
1946 });
1948 doc = headReplace(doc);
1949 doc = doc.toString().replace(/(\u000b|\u001c|\r)/gm, "").trim();
1950 //console.log(doc);
1951 let chunk = "";
1952 let numChunks = Math.ceil(doc.length / 1024);
1953 for (let i = 0, o = 0; i < numChunks; ++i, o += 1024) {
1954 chunk = doc.substr(o, 1024);
1955 conn.write(chunk);
1956 }
1957 conn.write(String.fromCharCode(28) + "\r\r" + '');
1958 conn.end();
1959 }
1960 }
1962 function eventCloseConn() {
1963 //console.log('connection from %s closed', remoteAddress);
1964 }
1966 function eventErrorConn(err) {
1967 //console.log('Connection %s error: %s', remoteAddress, err.message);
1968 }
1970 // Connection Events //
1971 conn.on('data', eventData);
1972 conn.once('close', eventCloseConn);
1973 conn.on('error', eventErrorConn);
1974 }
1976 function setUp(server) {
1977 server.on('connection', processConnection);
1978 server.listen(6661, 'localhost', function () {
1979 //console.log('server listening to %j', server.address());
1980 });
1981 }
1983 setUp(server);