United States v. Precision Medical Laboratories, Inc.
This text of 593 F.2d 434 (United States v. Precision Medical Laboratories, Inc.) is published on Counsel Stack Legal Research, covering Court of Appeals for the Second Circuit primary law. Counsel Stack provides free access to over 12 million legal documents including statutes, case law, regulations, and constitutions.
Opinion
PORT, District Judge:
Appellants, Precision Medical Laboratories, Inc. (Precision) and Elemer Gall (Gall) were found guilty1 after a four day jury trial in the Southern District of New York, Bonsai, Judge, of 77 counts charging the filing of false claims with the United States between July 2, 1976 and October 29, 1976 in connection with laboratory services performed for patients covered by the Medicare or Medicaid programs. The filing of such false claims violated 18 U.S.C. §§ 287 and 2.2 Appellants were also found guilty of 30 counts charging the receipt of checks in the mail in payment of such services in violation of 18 U.S.C. §§ 13413 and 2.
Sixty-three of the false-claim counts relate to claims made for Medicare payments on form SSA1490. The remaining 14 false-claim counts are based on claims under the Medicaid program.
Twenty-seven of the mail-fraud counts relate to the acknowledged receipt in the mail by Precision of checks in payment of [437]*437the alleged false and fraudulent Medicare claims, and three relate to the acknowledged receipt from the mails of checks in payment of the alleged Medicaid fraudulent claims.
Appellants Precision and Gall, who owned and controlled Precision, claim entitlement to a reversal of the resulting judgments of convictions on the grounds of insufficiency of the evidence and errors in the charge. A careful examination of the record on appeal convinces us that there is sufficient evidence to sustain the convictions and that Judge Bonsai’s charge is free of reversible error. Accordingly, we affirm.
I. SUFFICIENCY OF THE EVIDENCE
The parties stipulated a large part of the proof relating to the modus operandi of Medicare and Medicaid and the payment by the Department of Health, Education and Welfare (HEW) of the claims upon which the indictment was based. Viewing the facts and inferences to be drawn from all the evidence in the light most favorable to the Government, Glasser v. United States, 315 U.S. 60, 80, 62 S.Ct. 457, 86 L.Ed. 680 (1942), the jury might have found the following:
Congress created the Medicare and Medicaid programs pursuant to which the United States provides funds for medical services to eligible recipients.
Medicare
Under the Medicare program, HEW pays the entire cost of the services through reimbursement to Blue Cross and Blue Shield of Greater New York (Blue Cross), with whom HEW has contracted to administer the program. Blue Cross receives and pays claims on behalf of HEW.
As a provider of services, appellant Precision received payment for services by submitting to HEW one of the latter’s official forms designated “form SSA 1490, Request for Medicare Payment.” See, e. g., Appendix, Exhibit 57. The form has two parts. The upper part, identifying the patient and signed by him, requests that payment of the benefits be made to him or “to the party who accepts assignment below.” The lower part is completed and signed by the physician or supplier and provides information concerning the nature of the services sufficient to permit a correct charge to be established for them. It also contains an acceptance or refusal of the acceptance of an assignment of the claim. Precision accepted assignments on all Medicare claims. As a result, payment of benefits was made directly to it rather than to the patient.
Medicaid
The Medicaid Act deals with health services for the medically indigent under state promulgated plans supported in part by federal, state and local funds. The Westchester County Department of Social Services administers the plan for Westchester County. That department receives, processes and pays claims to the providers of services upon claims submitted by the providers. The claim form contains a certification stating in part “that the vendor understands that payment and satisfaction of this claim will be from Federal, State and local public funds and that he may be prosecuted under applicable Federal and State laws for any false claims, statements, or documents or concealment of a material fact.” See, e. g., Appendix, Exhibit 67. Upon certification by the New York State Department of Social Services, HEW reimburses the state for claims paid under the Medicaid program on the basis of fifty cents on the dollar.
The Claims
All the claims submitted by Precision for payment under the Medicare or Medicaid programs were paid in accordance with the information disclosed on the claim: in due course reimbursement was made by HEW to New York State and Blue Cross.
Equipment
The equipment used to analyze the blood specimens was essentially of two types. Precision used a relatively simple device [438]*438known as an Auto Analyzer II. This was capable of performing two tests simultaneously. St. Agnes Hospital in White Plains and Dianetics Medical Laboratory, Inc. in Syosset, New York employed more sophisticated equipment capable of performing as many as twenty tests on a single specimen at very high speeds. The equipment at St. Agnes was known as SMA or SMAC, Sequential Multiple Analysis Computer. Dianetics had similar equipment of a different manufacturer. The equipment at Precision is referred to as “manual”, that at St. Agnes and Dianetics as “automated”.
Fee Determination
The gist of the false claims and alleged fraud charged against appellants was that they submitted claims to Medicare and Medicaid for blood tests at rates payable for tests performed on manual equipment when in fact the tests were done on automated equipment. Blue Cross and Social Services maintained updated lists of hospitals, laboratories and other providers having the automated equipment. Both Medicare and Medicaid provided higher rates for tests performed on the manual equipment than on the automated equipment. In some instances the difference could be very substantial. For instance, a flat fee for a given series of tests performed on the automated equipment was reimbursed at from $12.50 to $20.00 while the same tests performed on the manual equipment and billed at the permissible individual rates per test could cumulate to $90 or $100.
To understand the method by which the allowable fees for services were determined by Blue Cross and Social Services in the case of Medicare and Medicaid respectively, it is necessary to detail some of the information required to be supplied by the provider to Blue Cross or Social Services. Question 7(b) of the Medicare claim form requires that the provider indicate where the services were rendered by a code given on the form indicating doctor’s office, nursing home, out-patient hospital or other location. Question 7(c) requires that the service furnished be described. In the case of separate blood analyses, each one would be described separately, or, if done on automated equipment, that would be indicated. In addition, Question 13 requires the supplier to “[s]how name and address of person or' facility which furnished service
Free access — add to your briefcase to read the full text and ask questions with AI
PORT, District Judge:
Appellants, Precision Medical Laboratories, Inc. (Precision) and Elemer Gall (Gall) were found guilty1 after a four day jury trial in the Southern District of New York, Bonsai, Judge, of 77 counts charging the filing of false claims with the United States between July 2, 1976 and October 29, 1976 in connection with laboratory services performed for patients covered by the Medicare or Medicaid programs. The filing of such false claims violated 18 U.S.C. §§ 287 and 2.2 Appellants were also found guilty of 30 counts charging the receipt of checks in the mail in payment of such services in violation of 18 U.S.C. §§ 13413 and 2.
Sixty-three of the false-claim counts relate to claims made for Medicare payments on form SSA1490. The remaining 14 false-claim counts are based on claims under the Medicaid program.
Twenty-seven of the mail-fraud counts relate to the acknowledged receipt in the mail by Precision of checks in payment of [437]*437the alleged false and fraudulent Medicare claims, and three relate to the acknowledged receipt from the mails of checks in payment of the alleged Medicaid fraudulent claims.
Appellants Precision and Gall, who owned and controlled Precision, claim entitlement to a reversal of the resulting judgments of convictions on the grounds of insufficiency of the evidence and errors in the charge. A careful examination of the record on appeal convinces us that there is sufficient evidence to sustain the convictions and that Judge Bonsai’s charge is free of reversible error. Accordingly, we affirm.
I. SUFFICIENCY OF THE EVIDENCE
The parties stipulated a large part of the proof relating to the modus operandi of Medicare and Medicaid and the payment by the Department of Health, Education and Welfare (HEW) of the claims upon which the indictment was based. Viewing the facts and inferences to be drawn from all the evidence in the light most favorable to the Government, Glasser v. United States, 315 U.S. 60, 80, 62 S.Ct. 457, 86 L.Ed. 680 (1942), the jury might have found the following:
Congress created the Medicare and Medicaid programs pursuant to which the United States provides funds for medical services to eligible recipients.
Medicare
Under the Medicare program, HEW pays the entire cost of the services through reimbursement to Blue Cross and Blue Shield of Greater New York (Blue Cross), with whom HEW has contracted to administer the program. Blue Cross receives and pays claims on behalf of HEW.
As a provider of services, appellant Precision received payment for services by submitting to HEW one of the latter’s official forms designated “form SSA 1490, Request for Medicare Payment.” See, e. g., Appendix, Exhibit 57. The form has two parts. The upper part, identifying the patient and signed by him, requests that payment of the benefits be made to him or “to the party who accepts assignment below.” The lower part is completed and signed by the physician or supplier and provides information concerning the nature of the services sufficient to permit a correct charge to be established for them. It also contains an acceptance or refusal of the acceptance of an assignment of the claim. Precision accepted assignments on all Medicare claims. As a result, payment of benefits was made directly to it rather than to the patient.
Medicaid
The Medicaid Act deals with health services for the medically indigent under state promulgated plans supported in part by federal, state and local funds. The Westchester County Department of Social Services administers the plan for Westchester County. That department receives, processes and pays claims to the providers of services upon claims submitted by the providers. The claim form contains a certification stating in part “that the vendor understands that payment and satisfaction of this claim will be from Federal, State and local public funds and that he may be prosecuted under applicable Federal and State laws for any false claims, statements, or documents or concealment of a material fact.” See, e. g., Appendix, Exhibit 67. Upon certification by the New York State Department of Social Services, HEW reimburses the state for claims paid under the Medicaid program on the basis of fifty cents on the dollar.
The Claims
All the claims submitted by Precision for payment under the Medicare or Medicaid programs were paid in accordance with the information disclosed on the claim: in due course reimbursement was made by HEW to New York State and Blue Cross.
Equipment
The equipment used to analyze the blood specimens was essentially of two types. Precision used a relatively simple device [438]*438known as an Auto Analyzer II. This was capable of performing two tests simultaneously. St. Agnes Hospital in White Plains and Dianetics Medical Laboratory, Inc. in Syosset, New York employed more sophisticated equipment capable of performing as many as twenty tests on a single specimen at very high speeds. The equipment at St. Agnes was known as SMA or SMAC, Sequential Multiple Analysis Computer. Dianetics had similar equipment of a different manufacturer. The equipment at Precision is referred to as “manual”, that at St. Agnes and Dianetics as “automated”.
Fee Determination
The gist of the false claims and alleged fraud charged against appellants was that they submitted claims to Medicare and Medicaid for blood tests at rates payable for tests performed on manual equipment when in fact the tests were done on automated equipment. Blue Cross and Social Services maintained updated lists of hospitals, laboratories and other providers having the automated equipment. Both Medicare and Medicaid provided higher rates for tests performed on the manual equipment than on the automated equipment. In some instances the difference could be very substantial. For instance, a flat fee for a given series of tests performed on the automated equipment was reimbursed at from $12.50 to $20.00 while the same tests performed on the manual equipment and billed at the permissible individual rates per test could cumulate to $90 or $100.
To understand the method by which the allowable fees for services were determined by Blue Cross and Social Services in the case of Medicare and Medicaid respectively, it is necessary to detail some of the information required to be supplied by the provider to Blue Cross or Social Services. Question 7(b) of the Medicare claim form requires that the provider indicate where the services were rendered by a code given on the form indicating doctor’s office, nursing home, out-patient hospital or other location. Question 7(c) requires that the service furnished be described. In the case of separate blood analyses, each one would be described separately, or, if done on automated equipment, that would be indicated. In addition, Question 13 requires the supplier to “[s]how name and address of person or' facility which furnished service (if other than your own office or patient’s home).” See, e. g., Appendix, Exhibit 57 (emphasis in original).
Blue Cross fixed the allowable fees for services by feeding the information supplied on the claim into a computer programmed to determine the allowable fee. In the event that blood tests were listed as separate items, the single or lower fee that applied to tests performed on the automated equipment would nevertheless attach, without regard to the number of tests done, where it appeared that they were done at a laboratory which used automated equipment. Absent information indicating a laboratory listed as using automated equipment or information indicating the use of automated equipment, the fees applicable to each individual test at the higher rate would be allowed. In the event a claim was received from an independent laboratory such as Precision not using automated equipment, and the claim indicated that the services were performed at a hospital or facility using automated equipment, the computer would not process the claim but would refer it to a special unit for investigation because of the inconsistency.
The Medicaid claims were authorized for payment by a visual examination of a claim form. Rates were fixed for the various services according to a state fee schedule which coded by number the various services. The auditor examined the claim form to determine that the recipient was eligible and then, based upon the code numbers listed for the services rendered, applied the fixed state fee schedule. Medicaid, like Medicare, had a lump sum payment for all tests performed on automated equipment. This is substantially less than the rates fixed for the same tests performed on man[439]*439ual equipment. The use of automated equipment was indicated by code number. In addition, Social Services has a list of laboratories using automated equipment. There is also a column on the form to indicate whether the services were performed at “home”, “office” or “hospital”. If “hospital” were indicated on a claim form of an independent laboratory, the. form would be routed to &■ special section for investigation and a determination that a mistake had or had not been made.
It thus becomes apparent that in order to correctly determine the fees due Precision, it was essential that not only the services performed be described correctly, but that the correct code numbers and the place where the services were performed be completely and correctly stated in response to the questions on the form.
Discussion
Since the first prong of appellants’ argument is addressed to the sufficiency of the evidence, a restatement of the factual issues claimed by appellants on the trial will help sort out the evidence on which the jury could have relied to support its guilty verdict:
At trial, the defense conceded that 1) there were different rates for tests conducted on the AA2 [manual] and the SMA and SMAC [automated]; 2) the tests specified in the indictment had been conducted on the SMA or SMAC or the equivalent, and 3) Precision billed and was paid in accordance with rates which the reimbursement agencies had made applicable to the AA2.
Thus, the only substantial issues at trial were whether Mr. Gall knew that there was a difference in rates depending on the kind of machinery used, whether he knew that Precision’s bills were not accurate in recording the place where services were rendered, and whether he intended to defraud the government.
Brief for Appellants at 6.
The jury could have also found (see Glasser v. United States, supra, 315 U.S. at 80, 62 S.Ct. 457, 86 L.Ed. 680):
Gall purchased Precision in March of 1974. He was supervisor of the chemistry laboratory at St. Agnes Hospital in White Plans prior to the time of the purchase. He also moonlighted as supervisor of the laboratory for Dr. Katz and Dr. Antonelle, the prior owners. After the formation of Precision, Gall continued as supervisor at St. Agnes and operated Precision through employees as a spare-time business. At the time of the purchase, Precision employed Madeline Franco, a laboratory technician, Ralph Taylor, as supervisor, and Mary Kahn Douglas, who was also employed by the doctors in a secretarial capacity. Initially, the work of the laboratory was confined to testing for patients of the vendor-doctors. Later, the work was augmented by including patients of a nearby nursing home and patients of a Dr. Roach. Initially, the work was done on manual equipment in the Precision laboratory. In June of 1975, Gall began using the laboratory at St. Agnes Hospital for a part of the work. In January 1976, he contracted with St. Agnes Hospital to perform blood chemistry tests for Precision at $3.50 per SMAC series. As earlier indicated, a SMAC series was a series of as many as 20 tests performed on a single blood sample at high speed by means of a computer which reported the results on a print-out. In June 1977, the work was switched from St. Agnes to Dianetics Medical Laboratory, Inc., located at Syosset, New York. Dianetics reduced the charge to Gall to $2.50 per series of tests similarly performed on high speed automated equipment with a computer print-out.
Although the usual practice at St. Agnes was to include the patient identity on the print-out, only in the case of Precision’s work was this information omitted at Gall’s direction. As a result, the print-outs for Precision’s patients could not be filed by St. Agnes in its alphabetical files of patients in accordance with its usual procedure.
[440]*440After the analyses were made, the printouts were taken by Gall to Precision where the results of only the particular tests ordered by the doctors were transferred to a log book under the patient’s name. The results were also indicated on the prescription or order blank of the physician. The print-outs were then secreted at Precision Laboratories with instructions to the employees that their presence was not to be made known. This practice was followed with the exception of orders from Dr. Roach. The print-outs in reference to his patients were delivered to him. It was this deviation from the usual practice which ultimately led to the discovery by Medicare and Medicaid that the work was being performed at St. Agnes rather than at Precision.4
The claims for both Medicare and Medicaid were in the same form during the entire time Gall owned Precision. Mrs. Douglas worked for Precision under Gall’s supervision for two hours daily. Her work was performed at home.
She prepared the claim forms from the laboratory slips showing the tests ordered. The fee column on the Medicare form was completed from a list of fees for the various tests given to her by Gall. The fees for the Medicaid forms were derived from a list of the codes and fees received from her predecessor before the laboratory was purchased by Gall. Code numbers and fees for other specific tests performed by the laboratory were obtained by phoning the Westchester County Medicaid Office. This information, she testified, was easily obtainable. Since she was never made aware by Gall that the tests were being performed at St. Agnes, she completed the Medicaid forms by (1) indicating that the services were performed at “0” for office, (2) leaving the name of the hospital blank where requested, and (3) listing the code numbers for the individual manual tests rather than the single code number indicating the use of automated equipment. The jury could infer that the code numbers were readily obtainable on a simple phone call. Monique Marion, too, filled in all the individual manual test code numbers, despite her knowledge that the tests were run at St. Agnes.5 Mrs. Douglas completed the Medicare claims in the same manner, indicating “place of service” in answer to 7(b) as “IL” and leaving Question 13 blank. She brought the completed forms to the office and delivered them to Gall for signature. In the event he was not there, she was authorized to sign them. Some of the claims were signed by him although not the particular claims forming the counts in the indictment.
From this evidence the jury could fairly infer that Gall was aware of and knew the contents of the claim forms, including the requirement of disclosing the place where the testing was actually done. The jury might further have found that since there was testimony that Gall knew that tests performed on the SMAC equipment was priced at a lower level than the individual tests, his failure to disclose this information to the actual bill preparers (1) was motivated by a desire to unlawfully obtain the higher fees, and (2) evidence a deliberate intent to defraud.
[441]*441At the time that Gall was supervisor of the laboratory prior to its purchase by him, the laboratory was inspected by Herbert Cupo of Blue Cross for the purpose of determining whether it operated with automated equipment. At the time Gall was called from his job at St. Agnes Hospital to the laboratory by Dr. Katz to confer with Cupo who testified that he told Gall the purpose of his visit and that the reason for such inspection in substance was that tests performed on the automated equipment were reimbursed at a lower level than those done on manual equipment. Gall argues that Cupo’s testimony was unworthy of belief. This is an argument more appropriately addressed to the jury, and it was. The jury obviously rejected it by their verdict.
The jury could have also found from Gall’s efforts to conceal the use of the St. Agnes laboratory that he was aware of the difference in the rates and also that Precision’s billing was being done on the basis of tests performed on manual equipment at the higher rates while he knew they in fact were being performed on automated equipment and should have been billed at the lower rates.
In sum, the secreting of the print-outs from the SMAC tests at St. Agnes; the delivery of the print-outs to Dr. Roach; the transfer of the information from the printouts to a log book indicating only the tests ordered but not all of those shown on the print-outs; the direction -to the laboratory technician Franco to never “ask anybody at St. Agnes anything about Precision Medical Labs. If you want to know anything, you talk to me or my brother,” Tr. 202; the running of daily controls on the Precision laboratory equipment when it was not being used in order to give it the appearance of daily use; the arranging for Taylor, a former supervisor, to come to the laboratory in response to a telephone call and to falsely represent himself as active laboratory supervisor in case of a visit by the state inspector; the payment to him on one occasion of $100.00 for such service; the instruction to Franco to falsely report to the state inspector that Taylor was on vacation on the occasion when he could not be located to play this role; the omission of the patients’ names from the information supplied to St. Agnes in connection with the blood samples submitted for analysis, as a consequence of which, the names of the patients could not be placed or located in the alphabetized files of St. Agnes Hospital; Gall’s statements to Grunte that St. Agnes tested only infrequently for Precision Laboratories and that since the patients’ names could not be located in the St. Agnes files, the tests could not have been done there for those patients; and the description of Gall as “a compulsive perfectionist type of man. In other words, he is not careless” by Dr. Ellner, a defense witness, Tr. 371 — all this the jury might have found was an effort to conceal the use of the automated equipment at St. Agnes and Dianetics because of the knowledge that Medicare and Medicaid were being billed at the higher fees for the use of manual equipment.
The claim forms not signed by the witness Douglas were identified by Monique Marion as having been signed by her with the authorization of Gall. She knew that the tests for which she was billing Medicare and Medicaid were performed at St. Agnes, outside the Precision laboratory. She testified that despite this knowledge she failed to indicate on either the Medicare or Medicaid claims that the hospital was involved in the testing because she was following the practice of her predecessor Douglas, and because Gall had not discussed the matter of billing with her. She excused her failure to complete Box 13 on the Medicare form by testifying that she never read or observed that box on the form. She testified .that if she had read it, she would have filled it in with the name of St. Agnes Hospital, because she knew that the tests were being performed there. She also testified that she was unaware that tests on manual equipment carried higher fees than those on automated equipment.
[442]*442She executed a large number of the Medicaid and Medicare claim forms. On the Medicare forms she signed them either to the right of Box 13 or under it, and in each form she filled in the date immediately under Box 13.6 Under these circumstances, although appellants (who offered her as a defense witness) insist that she exonerates them, the jury would be justified in refusing to credit her testimony that she was unaware of Box 13. In view of (1) her undisputed knowledge that the tests were performed at St. Agnes, (2) her very personal relationship with Gall, and (3) her admission that she would have disclosed St. Agnes’s connection in Box 13 if she was aware of it, the jury might have inferred that her failure to disclose it resulted from Gall’s instruction.
Our-scrutiny of the record convinces us there is no merit to appellants’ insufficiency-of-the-evidence claim.
II. FILING OF THE CLAIMS AND JURISDICTION
Appellants contend that since the Government failed to show that Gall signed any of the Medicare or Medicaid claim forms and failed to connect him with the actual filing of the claim, they cannot be guilty of submitting a false claim. This argument completely ignores the aider and abettor statute, 18 U.S.C. § 2.7 The evidence that Gall authorized the signing and filing of the claim forms by Mary Douglas and Monique Marion was uncontradicted. This evidence permitted the jury to find that appellants filed the claims.
For like reasons, appellant Gall claims he cannot be charged with knowledge of the contents of the claims or any false statements that were contained in them. That the jury could find otherwise is demonstrated in the earlier discussion of the facts.8
Appellant Gall next contends that since the claim forms executed by Precision were submitted to Blue Cross and Social Services, not directly to HEW, the Government failed to prove the filing of any false claim with an agency of the United States in violation of the statute; consequently, no jurisdiction existed for the prosecution.
United States v. Candella, 487 F.2d 1223 (2d Cir. 1973), cert. denied, 415 U.S. 977, 94 S.Ct. 1563, 39 L.Ed.2d 872 (1974), cited by appellants to support this position, holds to the contrary. In that case the false claims were contained in an affidavit and bill of lading submitted by the defendants to the City of New York, which in turn submitted its claim for reimbursement to the Department of Housing and Urban Development in much the same manner that Blue Cross and Social Services submit their claims for reimbursement to HEW. Additionally, with respect to one claim for less than $10,000, the claim and supporting papers submitted by the defendants did not (and were not required to) physically accompany the claim for reimbursement by the City. Even though the instruments actually containing defendants’ false statements were not part of the claims submitted to the governmental department, the conviction encompassing these counts was affirmed.
Based on the same facts here, appellants somehow find support in Candella for their argument that the district court lacked jurisdiction. Thé same contention in Candella was disposed by finding jurisdiction under 18 U.S.C. § 3237(a).9 In United States v. Catena, 500 F.2d 1319 (3d Cir.), cert. denied, 419 U.S. 1047, 95 S.Ct. 621, 42 L.Ed.2d 641 (1974), the court affirmed a conviction un[443]*443der 18 U.S.C. § 287 of the defendant physician for filing false claims under the Medicare program despite the filing by the defendant of the claim with Blue Shield and Travelers Insurance Company instead of directly with HEW. Travelers and Blue Shield were contractors of HEW for the servicing of medical claims. The convictions were sustained on the theory that the physician caused Blue Cross and Travelers to file the claims with HEW — this despite the absence of any reference to 18 U.S.C. § 2, the aider and abettor statute in the indictment.
III. THE CHARGE
Instruction on the Scienter Requirement
Appellant Gall finds error with the charge on the scienter requirement. Specifically, he asserts the trial judge
(1) failed to distinguish between “intent to defraud” and “knowingly, wilfully and unlawfully”,
(2) failed, over defense objection, to define and explain separately the terms “knowingly”, “wilfully”, and “unlawfully”,
(3) used, again over defense objection, the discredited and misleading term “recklessly”,
(4) having charged that knowledge of falsity can be inferred from “reckless” disregard of the truth,
(a) failed to include a balancing charge that actual belief in the truth of a statement negates knowledge of falsity, and
(b) failed to advise that conviction could result only if appellant also acted with a “conscious purpose to avoid learning the truth”, and finally,
(5) instructed that Mrs. Douglas and Miss Marion were acting for appellant, and thereby removed from the jury’s consideration the question of appellant’s knowledge.
We find these arguments wholly lacking in merit. Appellant was convicted under 18 U.S.C. §§ 287 and 1341. The scienter requirement in both of those sections is “knowledge”. To test the adequacy of the charge, we must view it in its entirety. Cupp v. Naughten, 414 U.S. 141, 146-47, 94 S.Ct. 396, 38 L.Ed.2d 368 (1973); United States v. Hanlon, 548 F.2d 1096, 1101 (2d Cir. 1977); United States v. Gentile, 530 F.2d 461, 469 (2d Cir.), cert. denied, 426 U.S. 936, 96 S.Ct. 2651, 49 L.Ed.2d 388 (1976); United States v. Bright, 517 F.2d 584, 588 (2d Cir. 1975); United States v. Catena, 500 F.2d 1319, 1324 (3d Cir.), cert. denied, 419 U.S. 1047, 95 S.Ct. 621, 42 L.Ed.2d 641 (1974). Thus viewed, the charge was overall clear and did not mislead the jury on what it must find regarding appellant’s state of mind in order to convict him.
Appellant makes much of the judge’s failure to give separate explanations for “intent to defraud”, “knowingly”, “wilfully”, and “unlawfully”. In our view, he exaggerates the importance of such omission, insofar as it exists. We find adequate the trial judge’s various explanations of the knowledge requirement:
(1) “The third element here’ is that the defendant . . . devised a scheme and knew what he was doing.” Tr. 556.
(2) “The third element again is that the defendant, Mr. Gall, acted . with specific intent to defraud. In other words, you must find that he had an intent here to deceive, to obtain this money by false pretenses.” Tr. 558.
(3) “[T]he really essential element in this whole case is Mr. Gall’s knowledge and intentions. The government must prove here that he did devise a scheme, that he intended to defraud.” Tr. 559.
(4) “An act is done knowingly and wilfully if it is done voluntarily or purposefully.” Tr. 559.
(5) “[Y]ou may find Mr. Gall acted wilfully and knowingly if you find that the claim was false and that Mr. Gall [444]*444knew that the claims were false, or that he acted with a deliberate disregard of whether the claims were true or false; in other words, that he closed his eyes to the truth here . . . Tr. 559-60.
(6) “An act is not done wilfully, knowingly or unlawfully if it is done by mistake, carelessness or other innocent reason.” Tr. 560.
Taken together and in context, these explanations could not possibly have misled the jury on the scienter requirement. If the words “wilfully” and “unlawfully”, found in the indictment but not the statute, had any effect at all, see United States v. Sirhan, 504 F.2d 818, 820 n. 3 (9th Cir. 1974) (difference between “knowingly” and “wilfully” more one of semantics than actual substance); White v. United States, 394 F.2d 49, 56 (9th Cir. 1968) (distinction between “knowingly” and “wilfully” held “of little weight”), it was to place a more exacting standard on what the Government had to prove. In United States v. Catena, 500 F.2d 1319 (3d Cir.), cert. denied, 419 U.S. 1047, 95 S.Ct. 621, 42 L.Ed.2d 641 (1974), a conviction for a violation of 18 U.S.C. § 287 was affirmed despite a much greater gap between the language of the indictment and the judge’s charge than we find here. In Catena the indictment tracked the statute and alleged that the defendant presented and caused to be presented to an agency of the United States a claim against the United States knowing it to be false, fictitious and fraudulent. The trial judge instructed in the language of 18 U.S.C. § 1001, instead of 18 U.S.C. § 287, that the jury could convict defendant Catena if it found that defendant knowingly made a false “claim to a matter within the jurisdiction of the United States.” 500 F.2d at 1324, Catena argued on appeal that the trial judge’s phrase, “claim to a matter within the jurisdiction of the United States,” was broader than the literal requirement of § 287 that the claim be submitted to a true agency of the United States, and therefore, that the use of this phrase permitted the jury to convict on findings which in themselves would not constitute a violation of § 287. Reading the charge as a whole, the Catena court found the explanation of the elements of the crime clear enough that it was “inconceivable” for the jury to have reached a different result. Likewise, we have read the entire charge here and find it “inconceivable” that the jury would have reached a different verdict had the charge been modified to meet appellant’s objections. See also Anderson v. United States, 417 U.S. 211, 228, 94 S.Ct. 2253, 2264, 41 L.Ed.2d 20, 33 (1974) (“Given the record, we think it inconceivable that, even if charged by more specific instructions, the jury could have found a conspiracy to cast false votes for local offices without finding a conspiracy to cast false votes for the federal officers as well.”).
We cannot accept appellant’s argument that failure “to distinguish these . crucial concepts” from one another, Brief for Appellants at 34, amounted to giving no instruction at all on the scienter requirement. All the cases cited by appellant for this argument are inapposite. In United States v. Byrd, 352 F.2d 570 (2d Cir. 1965), the trial judge omitted criminal intent entirely in charging the essential elements of the offense. We found such failure was tantamount to no instruction at all. But here Judge Bonsai charged, in various ways, that knowledge and intent were essential elements of the crime. See p. 443 supra. United States v. Pope, 561 F.2d 663 (6th Cir. 1977), involved a conviction for possession of illegal drugs with intent to distribute. As in Byrd, the charge omitted an essential element, intent to distribute.
Appellant urges that the one-time use of “recklessly” renders the entire charge on scienter defective. As appellant claims, United States v. Hanlon, 548 F.2d 1096, 1101 (2d Cir. 1977), disapproved the use of the term “reckless”. However, the repeated use of it in Hanlon did not constitute error — nor does the isolated use here constitute error, particularly where it was [445]*445preceded by the criterion that appellant act “with a deliberate disregard of whether the claims were true or false.” Tr. 560 (emphasis added). The Hanlon court was troubled with the prospect that the use of the term “reckless” might cause a jury to convict upon a finding of carelessness or negligence. Here, as in Hanlon, the trial judge was careful to avoid this possibility by charging, “An act is not done wilfully, knowingly, or unlawfully if it is done by mistake, carelessness or other innocent reason.” Tr. 560. In addition, the trial judge substituted deliberateness for recklessness.10 Id. Appellant also argues that, contrary to the rule in United States v. Morales, 577 F.2d 769, 774 (2d Cir. 1978), and United States v. Bright, 517 F.2d 584, 588 (2d Cir. 1975), the trial judge, after charging that knowledge of falsity can be inferred from “reckless” disregard of the truth, failed to give a balancing charge that actual belief in the truth of a statement negates knowledge of falsity. Assuming arguendo a “reckless disregard of the truth” charge, the record refutes appellant’s claim:
[Y]ou may find Mr. Gall acted wilfully and knowingly if you find that the claim was false and that Mr. Gall knew that the claims were false, or that he acted with a deliberate disregard of whether the claims were true or false; in other words, that he closed his eyes to the truth here; unless, of course, you find from the evidence that the defendant believed the claims to be true.
Tr. 559-60 (emphasis added). Morales, 577 F.2d at 774, and Bright, 517 F.2d at 588, require no more than this.
Appellant cites United States v. Hanlon, 548 F.2d 1096 (2d Cir. 1977), United States v. Sarantos, 455 F.2d 877, 880-82 (2d Cir. 1972), United States v. Squires, 440 F.2d 859, 864 n.12 (2d Cir. 1971), and United States v. Abrams, 427 F.2d 86, 91 (2d Cir.), cert. denied, 400 U.S. 832, 91 S.Ct. 64, 27 L.Ed.2d 63 (1970), for the following proposition: where a trial judge instructs a jury that it may infer guilty knowledge from reckless conduct, he must add an instruction that the jury may then convict the defendant only if he also acted “with a conscious purpose to avoid learning the truth.” Brief for Appellants at 40. The judge may not join these two points simply with the word “or”; he must state the concept in the conjunctive by using the word “and”. Assuming arguendo that the trial judge’s “What I am saying here” was the equivalent of “or”,11 appellant’s argument is without substance. The cited cases do not support the contention. Hanlon did not discuss the point. It noted only: “It is settled law that a finding of guilty knowledge may not be avoided by a showing that the defendant closed his eyes to what was going on about him; ‘see no evil’ is not a maxim in which the criminal defendant should take any comfort.” 548 F.2d at 1101. Next, Abrams merely found that its facts permitted a jury finding that the defendant acted with a “reckless disregard” of the truth and with a “conscious purpose” of avoiding it. It did not discuss the need for “reckless disregard” and “conscious purpose” as conjunctive conditions for conviction. Squires does not require a conjunctive statement of the “reckless disregard” and “conscious purpose” concepts either. Appellant’s cite to this case points to a footnote, 440 F.2d at [446]*446864 n.12, which emphasized the portion of the Abrams opinion stating that the jury could have ascribed to the defendant a reckless disregard and a conscious avoidance of the truth. But the Squires court faced a situation where the trial judge had failed altogether to instruct that if the jury found the defendant ignorant of the actual truth, it would have to find that the defendant acted with a conscious purpose of avoiding the truth before it could convict him. Hence, Squires cited Abrams for the general rule that a defendant may act “knowingly” despite actual lack of knowledge if he acts with a conscious purpose of avoiding the truth — not a rule that the concepts of “reckless disregard” and “conscious purpose” must appear conjunctively in the charge to the jury.
Finally, Sarantos explicitly faces and defeats appellant’s argument. Like our appellant, defendant Sarantos argued that the use of “or” instead of “and” to connect the concepts “reckless disregard” and “conscious purpose” in the charge required a reversal of his conviction. Sarantos answered:
We see no reason to take such drastic action. The phrases “reckless disregard of whether the statements made were true” and “conscious purpose to avoid learning the truth” mean essentially the same thing. . . . Therefore, any difference in meaning that might possibly result from the substitution of “or” for “and” would surely constitute harmless error. While we prefer the use of the connective “and” because we think the repetition better impresses on the jurors’ minds the importance of finding a deliberate disregard of the facts, we do not think our preference requires a new trial.
455 F.2d at 882 (citation omitted). See also United States v. Bright, 517 F.2d 584, 588 (2d Cir. 1975) (“We assume that the use of the disjunctive ‘or’ standing by itself would not require us to reverse.”). We thus proceed to the last of appellant’s attacks on the charge’s treatment of the scienter requirement.
After telling the jury that the first element of the crime is the filing of a false claim, the trial judge said,
Of course, the evidence does not show that Mr. Gall sent in these claims. It shows that, as I recall it, Mrs. Douglas and Miss Marion sent in these claims, but, of course, they were acting for Mr. Gall. He was running the laboratory, and they were purely his employees for the purpose of sending in the claims.
Tr. 555 (emphasis added). According to appellant, the italicized phrase amounted to a directed verdict that appellant knew what was on the forms. We disagree. The trial judge here was describing the first element of the offense, the making and filing of a false claim. He carefully noted what the evidence did not show, and then explained what the evidence did undisputably show. In this context, the instruction that those who actually submitted the claims “were acting for Mr. Gall” meant that simply because appellant had not sent in the false claims himself did not ipso facto exonerate him from guilt under 18 U.S.C. § 287.
Limiting Instruction on the “Similar Acts” Evidence
Appellant Gall terms as “similar acts” evidence the testimony of Taylor and Franco concerning the arrangements made by Gall with Taylor for the latter to pose as supervisor of the laboratory in ease of an inspection, or, in the event Taylor could not be located by Miss Franco, for her to report to the inspector that he was on vacation. Categorized in like manner was Leon Grunte’s testimony concerning Gall’s statements that (1) tests were done at St. Agnes only infrequently and (2) the absence of the patients’ records being sought from St. Agnes’ files indicated that the analyses were not done there. Appellant asserts that although Judge Bonsai instructed the jury that “in connection with the knowledge and intentions of Mr. Gall in making these claims” and that to determine his specific intentions they could consider the testimony of Miss Franco, Mr. Taylor and [447]*447Mr. Grunte, Tr. 561-62, his failure to instruct them that the use of this evidence was limited solely to that purpose requires reversal. Appellant’s major premise is wrong. The evidence which he demands should have been circumscribed is not “similar acts” evidence. It is evidence of the charge made in the indictment. The indictment in one set of counts charges appellants with the use of the mails in a scheme to defraud, and in the other set of counts with presenting and causing to be made and presented claims seeking payments at rates allowed for manually performed clinical laboratory tests when appellants knew the claims were false and fraudulent because the tests were in fact performed on automated equipment carrying a lesser pay rate.
The evidence to which appellant Gall objects directly supports the allegation that there was a scheme to defraud and the charge that the claims were false and fraudulent in reporting the tests at the higher rate for manual equipment when, in fact, the tests were performed on automated equipment. What the court stated in United States v. Papadakis, 510 F.2d 287 (2d Cir.), cert. denied, 421 U.S. 950, 95 S.Ct. 1682, 44 L.Ed.2d 104 (1975), cited by appellant, is particularly apt here: “In any event, on our analysis, the evidence was itself probative of the [crime] charged in the indictment.” 510 F.2d at 295. Although we do not consider the evidence that appellant claims should have been circumscribed by a limiting instruction as “similar acts” evidence, nevertheless, the court did instruct the jury that the testimony of Taylor, Franco and Grunte concerning efforts of Gall to conceal the use of the St. Agnes laboratory was to be considered by them in connection with Gall’s knowledge and intentions. Tr. 561-62. The testimony did not, as appellant Gall claims, prejudice appellants by ascribing “bad character” to Gall. It was clearly relevant and not unfairly prejudicial. See Fed.R. Evid. 401, 403.
Appellants’ remaining contentions are of insufficient merit to require discussion. They were found guilty after a full and fair trial on ample and convincing evidence, and the convictions are affirmed.
APPENDIX
Exhibit 57: “Request for Medicare Payment” (Form SSA 1490)
Exhibit 67: “Authorization and Claim for Professional Services and Supplies”
Illustrations to follow.
[448]*448
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" width="1307"/>
[449]*449
[450]*450ovo < i £3 _ M u • ■: o : !■ « i — C** LCV P VO clT P O ir ir :o § M - U> í/í S I g i+» S :a c ir. cv M. VO cv VO ctf • 0) ir cv ff O tr O • O O o o 00 (0 <u o o • irv <9 ir CV) ir r— r— P VO CV p o c H • P (ti P •o .0) <i) > < o ir +» ir o o O r-P, • W ÍH O • .ai p ; a íh Lfi. W m O cv +» t- a o o « VO o VO CS VO «ti o o es <§> CD o cv cv cr @) CD VO CV PP s p o (ti o x p p o PH te co es r-* hP V* Sí pi cv vn P vr cv p 0) en 2 (ti P, o c 0) E" C o •H +> c 0) +> ft <D ft X (0 43 TÍ O 43 tí P > C0 p •H G £ o •§E co <1> 2 43 O O P H P En b0< PCO OtíH <9 S fc •O O H P H Eh 3 H CC IDOU <M O G O O E P. 3 43 P •O P 0) Duí E< OO < CD W «es 02 ü w ^ £0 ^ u 73 4> 43 tí CTv 43 ft W 5> H £ O rl O CO 43 H ft <m rlO £ ft O G Cd ft P +5 10 P 3 ft W <9 O <M cd 0) TÍ «í O. rH G £ ftB 03 O P P,P <9 C tí 3 43 P S to M « • TÍ P 73 <9 73 03 O (9 O G Cd +5 G <d H ft O (ti Tí C 73 W > G ft <9 tí tí co o o o Iti Orí (9 O > H > P Cd ft (ti cd a (9 ft P 43 C co 43 O tí 73 73 X «03 <9 <9 0) <9 Cft N 73 ft tí * cti cd (9 E P E O 43 (9 cd P P P C0 (9 TÍ P 43 P <M P P O 10 73 cti <9 G ft ft M •H Cti O > H 73 «h P. bC G <9 a c co h <h 3 tí H p C0 S W 3 tí O Oftp 73 <9 C73ft CP cti G tí P Cti «M *H W O P S <9 <9 G O 3 P (9 <9 •H 73 C E O > <9 >i C ft <9 E cti cd <9 ft >> O, tí co <ti (ti H aw a "73 cd E <9 <9 -P O ft P Cti 73 O cd co p <9 O TÍ P P c rH (X <9 -P (9 19 Cti C0 73 t> P P P TÍ O p C cd cti co 3 0, cd >s O tí) p ftECH tí Cd (9 (9 P 19 to ft ft 0) P <9 <9 <9 P HP O P CO 3 P cd 73 (H -P P (9 -P cd p cd P <ft o P P O C0 P ft <9 , A <m p <9 C0 P O P H (9 p P G cd o p “ 73 (0 ft <9 O TÍ t> > C ft TÍ <9 bO co >. c cti <9 VJ X O. E 73 G ft P G «3 O >. ft cti X C cd W cd O.P 73 S <9 G G <9 bTQ (9 3 SC £ ft, •H (9 t»5 4) 73 P Cti O P ft cd O.-H p Cd P H u co p p ft >9 cd 3 (9 ft (9 P O, 73 P P C 73 P H 3 <9 (0 Cti P ft 73 O co w O G O , H tí (ti H cd c >.p 3 ft O (0 73 73 3 C ft C •H ft. 4» 4) Cd > W.73 H (9 (ti C Oí 73 P 3 P G w cd TÍ H 4) ft P H O O W O TÍ TÍ 73 P S > G « ft (9 H 73 C 4) > Cd <9 O to ft 73 tí <9 <9 •H p H P 73 > cd cd P 4) O E H fc ft ft O P O, O O Cti E ft, C0 P O co C P ft (9 rl H ft« Tí (ti 73 H 73 O C 4) O. G O Cti P O, Cti H 3 *«H CO « 4) P H P P (0 TÍ 73 P.P (9 S G 4) 3 cd 4sí co o1 E cd 4) tí CO 43 ft cd <9 P I — I H O olt»! o tí H *rí Cd > H C0| E W ft TÍ >-■ TÍ 43 S (0 P C0 <9 4) p E ft O « (ti O H ft 43 ft ft, > O ft bC <9 ft <d O ft 4) G O ft (9 CO O ap tí ft, p H P O 73 cd o TÍ 73 TÍ cd P cd 4) O «w C o E o co 4) *H *rl CO "H P 73 Cd P X 4) H ft Cd <9 E O O C0 «p O 10 C E 4) P rlrí O cd P 3 h cd co o o. C 73 >3 CO ft C (9 TÍ cd o p •H C0 ft > 3 O ft-r-S ft, (9 co >. to H S H cd • cd • H p O C0 O tí 73 <9 Cd 73 ft P ft, 4) O cd E o P H <9 tO (ti tO ft •H cd 73 ft H > G 4) C cd (ti P Cd O (ti TÍ TÍ H E O 73 cd tí (9 ft Cd CO E <9 >i p cd cd ~ C P H 4) tirl p E P a cd h co o Cd 73 c TÍ 43 4) P H O H o, c ft d O- O -H P cd o p p ft ft ft 4) C <9 O O tí 73 G W G (9 3 P 4> H C 4) -H 73 4> P fti 4) E P 3 <9 C 3 O > O O O <ti 0) 73 P 4) CO ft O ft <9 (ti c* ft O ft H| O, « cd co co ü G * 0) P o P C H TÍ 43 Cd P >J E p Cd Cti 43 tí O E P P, TÍ cd co ft^ DATE CLAIMANTS SIGNATURE TITLE SPECIALTY
Related
Cite This Page — Counsel Stack
593 F.2d 434, Counsel Stack Legal Research, https://law.counselstack.com/opinion/united-states-v-precision-medical-laboratories-inc-ca2-1978.