Physician Management in Primary Care BARBARA S. HULKA, MD, LAWRENCE L. KUPPER, PHD, AND JOHN C. CASSEL, MD

Abstract: Minimal explicit consensus criteria in the management of patients with four indicator conditions were established by an ad hoc committee of primary care physicians practicing in different locations. These criteria were then applied to the practices of primary care physicians located in a single community by abstracting medical records and obtaining questionnaire data about patients with the indicator conditions. A standardized management score for each physician was used as the dependent variable in stepwise regression analysis with physician/practice and patient/disease characteristics as the candidate independent variables.

For all physicians combined, the mean management scores were high, ranging from .78 to .93 for the four conditions. For two of the conditions, care of the normal infant and pregnant woman, the management scores were better for pediatricians and obstetricians respectively than for family physicians. For the other two conditions, adult onset diabetes and congestive heart failure, there were no differences between the management scores of family physicians and internists. Patient/disease characteristics did not contribute significantly to explaining the variation in the standardized management scores. (Am. J. Public Health 66:1173-1 179, 1976)

Although the major thrust of peer review and PSRO activities has centered on hospital based medical care, an obvious extension of these evaluation efforts will be in the sphere of ambulatory care, the bulk of which is provided through office based physicians in private practice. Already several research investigations have focused on ambulatory care, with the intent of defining appropriate criteria and methodologies for evaluation.'-9 Problems of record keeping, which have plagued hospital based studies, are multiplied many fold when office practice is at issue. Even more critical than the operational difficulties of data collection are the conceptual issues of what aspects of performance reflect on quality and should be the subject for measurement. The most common tack has been to identify indicator conditions, diseases or physiologic states, which are commonly seen in office practice and about which there is some consensus as to the appropriate criteria for diagnosis or management.0'"1 The methods for deriving these criteria have varied, as have the length of the criteria lists derived. If management criteria are intended to apply to the large majority of cases of a given condition, irrespective of case severity, then the lists become abbreviated to a basic minimum. When management criteria reach a minimal level of acceptability, one might expect that such a large proportion of physicians

would be in conformance with the criteria that no variability among physicians could be demonstrated, resulting in the dilemma of interpretation: either all physicians perform adequately or the criteria are too minimal to discriminate. The current study is addressed to the development of minimally acceptable criteria sets in the management of four indicator conditions, to the application of these criteria in private practice office settings, and to testing the hypothesis that explicit consensus criteria, although minimal both quantitatively and qualitatively, can disciminate among varying levels of physician performance, and that the variation can be associated with specific characteristics of physicians and their practices.

From the Departments of Epidemiology and Biostatistics, University of North Carolina. Address reprint requests to Dr. Barbara S. Hulka, Associate Professor, Department of Epidemiology, University of North Carolina, Chapel Hill, NC 27514. This paper, submitted to the Journal June 2, 1976, was revised and accepted for publication August 10, 1976.

AJPH December, 1976, Vol. 66, No. 12

Background For the past several years, the Department of Epidemiology at the University of North Carolina has been engaged in research designed to study the "Organization, Utilization and Assessment of Primary Medical Care."'0' '2 The area of assessment, although the most difficult to conceptualize and to implement, was also recognized as the basic core of the research. This paper represents one of a series of reports addressed to the issue of practice assessment.'3 The assessment design utilized the indicator case model, in which physician management was only one of eight elements. The other elements included utilization, cost/convenience, communication from physician to patient, physician awareness of patient concerns, patient compliance, patient satisfaction, and patient outcomes. The indicator conditions 1173

HULKA, ET AL.

to which this model was applied were adult onset diabetes mellitus, congestive heart failure, the normal pregnant woman, and the normal newborn during the first year of life. Admission criteria were established for each condition for the purpose of reducing heterogeneity among patients and to facilitate comparability of data collection. Patients with the indicator conditions were identified from the offices of physicians practicing in the areas of family medicine/general practice, internal medicine, pediatrics. and obstetrics. All such physicians practicing in a single community of approximately 200,000 people were identified through the roster of the County Medical Society. Random sampling procedures were used to order physicians in the sequence in which they would be asked to participate. Overall physician acceptance and continuance with the study was 68 per cent resulting in the inclusion of 34 family physicians, 11 internists, 8 pediatricians, and 8 obstetricians. Patients were enrolled into the study at the time of an office visit to these practitioners; an 84 per cent acceptance rate was achieved which included 523 infants, 363 pregnant women, 244 diabetics, and 128 patients with congestive heart

failure.

Methods I. Criteria setting A minimum basic set of explicit consensus criteria were developed over a period of several months and many meetings between physician clinicians and researchers. A core nucleus of four family physicians as well as physicians in other primary care disciplines were consistently involved along with consultant practitioners and researchers on an ad hoc

basis. Following an initial literature review and preliminary discussions, the components of each management protocol were agreed upon, the weighting of components reviewed, and an overall scoring plan was established. The considerations pertaining to each of these decisions were numerous. To enumerate a few: a. Minimum criteria were agreed upon in order that they should be applicable to almost all patients with the indicator conditions, irrespective of demographic characteristics and disease severity. Certain "branching" features were allowed in order that relevance could be maintained for individual patients. (For example, instructions on how to administer insulin were only applicable to insulin-dependent diabetics.) b. Differential weighting of individual criteria within the overall management score was minimized, since weighting per se is an arbitrary procedure. Where weightings were applied, they were based on a determination of clinical importance in patient management and outcome. Secondarily, the probable reliability of the data and the observed variability were considered. c. An overall management score whereby patients, physicians, or practices could be accurately compared 1174

was the objective. Standardization of the score to account for differing numbers of patients per doctor was required in order to make comparisons among

physicians.

2. Data Collection Data were collected from two sources, the medical record and physician questionnaire. The questionnaire format was necessary in order to obtain information on items not usually included in the medical record, such as the medical instructions given to the patient. The physician was supplied with a list of instructions pertinent to the particular indicator condition for each patient in the study. For each instructional item, the physician checked whether or not the patient had been informed in that particular area. This questionnaire was completed within a few hours to days after the patient visit at which the patient had been enrolled in the study. Medical record data were obtained over a variable time period depending on the particular indicator condition. For diabetes and congestive heart failure the time interval was six months from the time of patient enrollment, for pregnancy it included all antepartum visits prior to delivery, and for infancy the time interval included all visits up to the I I th month birthday of the child. Abstract forms were completed by nurse-abstractors for each office visit occurring during the time interval of the study. 3. Management Scores The specific components of the management scores for each indicator condition are listed in Appendix A. The components fall into three categories: instructions, physical examination, and history. For infancy, a fourth category, immunizations, has been added. The instructional criteria were devised to be relevant to most patients with the particular conditions. Examples of non-relevant items included "type of formula" for breat fed infants or "type of syringe" for diabetics not using insulin. Data on whether or not instructions had been provided were obtained from the physician questionnaire. Data on criteria pertaining to physical examination, laboratory, and immunizations were obtained from the medical record. Compared to criteria sets published elsewhere, the extremely minimal nature of these criteria is immediately evident. The rationale for these minimal criteria was discussed previously under "criteria setting". In addition, criteria selection was based not only on what was clinically relevant, but also on what was expected to be available in the medical record. The next decision concerned weighting of each criterion. Since a decision concerning differential clinical relevance of each criterion for all types of patients was felt to be arbitrary, the weightings applied were based primarily on the data source. Record data were assumed to be more stable than that obtained from physician questionnaires. Therefore, each item that pertained to physical examination, laboratory work, or immunizations was given twice the weighting of the

instructional items. A score was then computed for each patient. The denominator of that score was the maximum number of points (weighted criteria) relevant to the individual patient and the numerator was the sum of the weights over all criteria acAJPH December, 1976, Vol. 66, No. 12

PHYSICIAN MANAGEMENT IN PRIMARY CARE

tually present. The resulting score was a proportion, ranging from 0 to 1; the higher the score, the better the management. One potential problem with this score is that the number of office visits during the study period varied for different patients. Clearly, the greater the number of visits, the greater the opportunity for performing a specified laboratory test or examination procedure. Therefore, the distribution of number of visits per patient for each indicator condition was reviewed. Only for five infants and one congestive failure patient were the number of visits insufficient to permit conformance with all criteria. Since the number of patients whose management score could be biased by this deficit in visits was so small, and since the number of visits required was so few (two for congestive failure patients and three for infants), one might assume that the absence of this minimum number of visits in itself represented inadequate care. For these reasons, no adjustment in individual patient scores was made for these six patients with an inadequate number of visits. A management score was calculated for each physician as the mean of his patients' scores. This mean management score suffered from the deficiency that the number of patients per physician varied, which resulted in marked differences in the variances of these mean scores. Secondly, the scores were skewed, with the majority at the "high" performance end of the scale. Therefore, a standardized score was calculated for each physician for each indicator condition. The formula for standardization follows: Xj

-

ni

X

N

where, x; = mean of all patient scores for the ith MD, x = mean of all patient scores for all MDs, n, = the number of patients for the ith MD, N = total number of patients for all MDs, S = standard deviation of all individual patient scores, Z = standardized score for the ith MD for each indicator condition.

The standardization procedure tended to equalize the variance among physician scores, and the resulting standardized scores were approximately normally distributed. In addition, the standardization procedure had the effect of accentuating the contribution of physicians with a large number of patients relative to physicians with small numbers of patients. For example, if a physician had a mean score based on only two patients which was greater than the overall mean x, and another physician had the exact same mean score based on 10 patients, the standardized scores would be such that the ten-patient physician would have a more positive standardized score than the two-patient physician; similarly, if these same two physicians had equal mean scores which were less than x, then the ten-patient physician would have a more negative standardized score than the two-

patient physician. AJPH December, 1976, Vol. 66, No. 12

Results Table I shows the means of the physicians' mean scores, the range in scores, and the numbers of patients and doctors on which the statistics are based. Judging by the mean management scores for each indicator condition, the overall level of physician performance is high. However, significant variability is seen both in the range of scores for individual physicians and in the number of patients per physician. In order to make comparisons among physicians supplying varying numbers of patients to the study, standardized scores were created for each physician for each indicator condition. To identify those characteristics of physicians and their practices, or patients and their diseases, which might account for the variability in standardized management scores, stepwise regression analysis was chosen as a reasonable statistical procedure for identifying important independent variables. This procedure allows for the inclusion in the model at any given step that independent variable which is most highly associated with the dependent variable controlling for the effects of all other significant independent variables which have already entered the model in previous steps. The dependent variables are the standardized physician management scores for each indicator condition. Two sets of candidate independent variables are identified: those relating to physician and practice characteristics, and the patient and disease related variables. Both sets of candidate variables appear in Appendix A. Mean values of continuous variables and 0,1 values of dichotomous variables are used in the regression equations. Essentially no risk factors or disease relevant variables were candidate independent variables for infancy and pregnancy, since admission criteria to the study ensured the inclusion of essentially normal patients. Table 2 presents a summary of the results of the regression analyses. For each indicator condition, the number of physicians (equivalently, the sample size) is given. The next

column lists the independent variables which sequentially entered each model at a p value less than .01. A conservative approach was adopted to insure a reasonable ""overall" significance level.'4 The numbers in the R2 column indicate the proportion of the variability in the standardized management scores explained by the model containing the particular set of independent variables presented in the table.* In reviewing Table 2, a clear distinction appears between infancy and pregnancy versus diabetes and congestive heart failure. In the management of infants and pregnant women, pediatrician and obstetrician respectively are the first variables to enter the model. The R2 values produced are .44 and .46. The addition of decreased length of practice for infancy increases the R2 value to .58. In pregnancy, increased number of personnel per MD enters the model (al-

*R2 is equal to the ratio of the reduction in the sum of squares of deviations of observed from predicted values obtained by using the given linear model to the total sum of squares of deviations about the sample mean of the dependent variable. -1175

HULKA, ET AL. TABLE 1-Physicians' Mean Management Scores by Indicator Condition Indicator

Condition

Infancy Pregnancy Diabetes Mellitus Congestive Heart Failure

No. of MDs

No. of Patfents

Range in No. of Pts/MD

40 38 41

474 340 234

1-38 1-32 1-28

.93 .92 .88

.66-1.00 .78-.99 .26-1.00

34

119

1-11

.78

.33-1.00

Mean Scores

Range in Scores

though at a significance level greater than .01), and the R2 becomes .54. For both conditions, specialty status of the physician is the first variable to enter each model and this variable in itself explains a very significant proportion of the variation in the level of the management scores. As can be seen, however, for the two chronic diseases, diabetes mellitus and congestive heart failure, neither physician nor patient characteristics are significantly correlated with management scores. These points are further illustrated in Table 3, in which the distributions of standardized management scores by type of physician are shown for each indicator condition. For infancy and pregnancy, pediatricians and obstetricians cluster at the higher scores compared to family physicians. For diabetes and congestive heart failure, there are no apparent differences by type of physician. TABLE 2-Regression Analysis with Physicians' Standardized Management Scores as Dependent Variables Indicator

Condition

Independent

No. of MDs

R2

Pediatrician

41

------------------------------

.438 .575 .464 .545 insig.

34

------------------------------

insig.

40

Infancy

Variables l Length of practice

38

Pregnancy

Obstetrician

*T No. of personnel/MD Diabetes Mellitus Congestive Heart Failure

*Significance level: .05 < p < .10

Discussion Methods for developing explicit process criteria in the evaluation of medical care have varied, along with the extent and precision of the criteria produced.' 3. 6 8. 9In the current study, explicit process criteria were developed using an informal group setting, with a small but consistent group of practitioners meeting on numerous occasions over an extended time period to achieve an eventual consensus on minimal management criteria for the care of four indicator conditions. Particular constraints must be considered when establishing management criteria for medical problems seen in the office setting. The adequacy of records is a problem, when no consistent record format may exist either within or between practices. Clinically pertinent criteria may be inconsistently recorded, such that they are useless for assessment purposes. Therefore, the choice of criteria must be based both on clinical decisions as to what constitutes good care and also practical considerations as to what kind of data can be consistently obtained. Alternative data sources exist: observation, interview, and questionnaire, the latter of which was used in the current study. Although physician cooperation was good, as measured by the rate of completed questionnaires (over 95 per cent usable data), the transferability of this technique is limited. It is not likely that physicians will find completion of special questionnaires on individual patients acceptable as a continuing means of patient care assessment.9 More feasible may be the introduction of a medical record format which stimulates the recording of pertinent data on all patients seen in ambulatory care settings. Review of the physicians' mean management scores indicated that the physicians were performing well on the measured components of management. The average scores for all physicians ranged from .78 to .93 on the four indicator conditions. However, overall averages give little information on the distribution of scores for individual doctors. Due to the varying number of patients per physician a standardized score was created. With these minimal process criteria sets, differences among physicians could be identified for two of the four indicator conditions. For infancy and pregnancy, level of management varied for pediatricians and obstetricians as com-

TABLE 3-Distribution of Physicians' Standardized Management Scores by Indicator Condition and Type of Physician Scores

(+)4.01to6 (+)2.01 to4 (+)0.01 to2

(-)1.99to0 (-)3.99 to (-)2 (-)5.99 to (-)4 (-)6.99to(-)6 TOTAL

1176

F.P.

1

5 15 6 4 1 32

Infancy PED.

8 0 0 0 0 0 8

Pregnancy OB.

F.P.

Diabetes F.P. INT.

0 0 5 16 8 1

3 2 1 2 0 0

1 14 12 3

0

1 5 4 0 1

30

8

30

11

CHF F.P.

INT.

1 8 11 3

2 4 4 1

23

11

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PHYSICIAN MANAGEMENT IN PRIMARY CARE

pared to family physicians. This distinction did not occur with adult onset diabetes mellitus and congestive heart failure. Family physicians and internists performed about equally well. Consistent with these results are the findings from a previous report in which measures of the doctor-patient relationship were the elements of interest.'3 Specifically, communication from physician to patient, physician awareness of patient concerns about his condition, and patient satisfaction were reviewed. The differences between pediatricians and obstetricians versus family physicians were most pronounced for the communication measure in infancy and pregnancy. Also, mothers of infants were more satisfied with physicians who had been trained in AMA approved residency programs, a variable highly correlated with pediatrician status. No differences by type of physician were found among patients with diabetes mellitus and congestive heart failure. A number of reasons might be advanced to explain these findings. One might be concerned about the reliability and appropriateness of the criteria, data collection and scoring methods, which could result in some unidentified but systematic bias in the data. This explanation is unlikely when one considers both the consistency of the associations over a variety of measurements (doctor-patient relationship variables, as well as management) and the relative strength of the association. It is more likely that the management criteria were not sufficiently sensitive to identify differences among physicians in their care of patients with congestive heart failure and diabetes. For these conditions the clinical case mix was great in terms of disease severity and therapeutic needs. For a heterogeneous group of patients more refined criteria, specific for variation in case severity, may be required. If record keeping were consistently better in the offices of pediatricians and obstetricians as compared to family physicians, then the differences in management scores might merely reflect a difference in quality of records. Since this possibility was not specifically investigated, the issue cannot be resolved. However, variation in record quality was not sufficient to produce differences in management scores between internists and family physicians. An additional variable, decreasing length of practice, was associated with improved management scores in infancy. As expected, that variable was highly correlated with physician age. When the regression analysis was repeated without length of practice as a candidate independent variable, physician age was the second variable to enter the model. Younger physicians had better management scores than older physicians. A cautionary point in interpretation is that comparisons were made among a relatively small number of physicians in one geographic locality. Although efforts were made to select physicians randomly for the study, refusals among physicians necessarily resulted in some selective processes. How self selection may have operated to affect the comparisons made would be difficult to substantiate. The participation rates varied somewhat by specialty: family physicians 34/53 (64.1 per cent), obstetricians 8/11 (72.7 per cent), pediatricians 8/9 (88.9 per cent), internists 11/17 (64.7 per cent). Although we have spoken of family physicians in this reAJPH December, 1976, Vol. 66, No. 12

port, many of these physicians may consider themselves general practitioners. During the early 1970s, there has been a change, not only in the name of the American Academy of Family Physicians from the previous name of the American Academy of General Practitioners, but also there has been a shifting emphasis in the training and expected practice roles of the family physician. As current residents in the family practice residency programs graduate and become practitioners, the emphasis and mode of practice may change as well. Lastly, it should be noted that this report has concentrated on the relationships between physician/practice characteristics and patient/disease characteristics, as these may affect the processes of care. Although differences in level of management (process) have been demonstrated with certain conditions although not with others, no attempt has been made to estimate the impact of these differences on the final arbitrator of effectiveness, and that is patient outcomes. These data are available from this study and are currently being analyzed.

REFERENCES 1. Brook, R. H. Quality of Care Assessment: A Comparison of Five Methods of Peer Review. Washington: National Center for Health Services Research and Development, 1973. 2. Peterson, 0. L., Andrews, L. P., Spain, R. S., Greenberg, B. G. An analytical study of North Carolina general practice. Journal of Medical Education, 31:1, 1956. 3. Kaplan, D., Weiner, M., Plotz, C. M. Suggested criteria for evaluation of physicians in family practice. Bulletin New York Academy of Medicine, 51:401, 1975. 4. Morehead, M. A. The medical audit as an operational tool. Am. J. Public Health, 57:1643, 1967. 5. Morehead, M. A., Donaldson. R. Quality of clinical management of disease in comprehensive neighborhood health centers. Medical Care, 12:301, 1974. 6. Payne, B. C., Lyons, T. F. Office Care Study. Ann Arbor: University of Michigan School of Medicine, 1972. 7. Sibley, J. C., Spitzer, W. O., Rudnick, K. V., et. al. Quality-ofcare appraisal in primary care: A quantitative method. Annals of Internal Medicine, 83:46, 1975. 8. Osborne, C. E., Thompson, H. C. Criteria for evaluation of ambulatory child health care by chart audit: Development and testing of a methodology. Pediatrics, 56:625, 1975. 9. Hare, R. L., Barnoon, S. Medical Care Appraisal and Quality Assurance in the Office Practice of Internal Medicine. American Society of Internal Medicine, 1973. 10. Hulka, B. S., Cassel, J. C. The AAFP-UNC study of the organization, utilization and assessment of primary medical care. Am. J. Public Health, 63:494, 1973. 11. Kessner, D. M., Kalk, C. E., Singer, J. Assessing health quality-the case for tracers. N. Eng. Med., 288:189, 1973. 12. Burdette, J. A., Babineau, R. A., Mayo, F., Hulka, B. S., Cassel, J. C. Primary medical care evaluation; the AAFP-UNC collaborative study. JAMA, 230:1668, 1974. 13. Hulka, B. S., Kupper, L. L., Cassel, J. C., Babineau, R. A. Practice characteristics and quality of primary medical care: The doctor-patient relationship. Medical Care, 13:808, 1975. 14. Kupper, L. L., Stewart, J. R., Williams, K. A. A note on controlling significance levels in stepwise regression. Am. J. of Epidemiology, 103:13, 1976.

ACKNOWLEDGMENT The project upon which this publication is based was performed pursuant to Grant No. HS00026-05 between the National Center for Health Services Research and the Department of Epidemiology, University of North Carolina. 1177

HULKA, ET AL.

APPENDIX A

Components of Management Scores

I. Infancy Instructions Condition at birth Feeding schedule Formula Frequency Adding foods Need for immunizations How to get emergency care Baby's weight Baby's development Frequency of return visits Multivitamins recommended

Physical Examination Recorded Weight

at least 3 times

Length Jduring study period

Ill. Diabetes Mellitus

11. Pregnancy Instructions

IV. Congestive Heart Failure Instructions

Instructions

Expected date of confinement Weight control Salt restriction Calorie restriction Nutritionally adequate diet Name of hospital for delivery How to get emergency care What to do about cramping or bleeding Frequency of return visits

Physical Examination Clinical pelvimetry Presentation of fetus Fetal heart rate-last tri-

Spacing/regularity of food intake Weight control How to get emergency care Frequency of return visits Symptoms of hypoglycemia What to do about hypoglycemia What to do about infection, illness, or vomiting Urine testing for sugar Care of feet Urine testing for acetone Carry diabetic identification Type of syringe Rotating injection sites

Physical Examination Weight Blood pressure

pressure

2nd and 3rd tri-

Weight J mester Preeclampsia-if present, evidence of Rx

Immunizations Polio (3 doses) DPT (3 doses)

Laboratory Urinalysis-2nd and 3rd trimester

Physical Examination Blood pressure Recorded Weight or at least edema 2 times Exam of during heart study Exam of period lungs

mester

Blood

Diet-low fat Diet-low salt Activity limitation How to get emergency care Frequency of return visits

Laboratory Urine or blood test for sugar

Serology Pap smear Hgb or Hct ABO blood type Rh Coombs Test in last trimester for Rh negative women

1178

AJPH December, 1976, Vol. 66, No. 12

PHYSICIAN MANAGEMENT IN PRIMARY CARE

APPENDIX A (continued)

Candidate Variables for Regression Analysis 1. Physician and Practice Characteristics Specialty status-family physician or not family physician (pediatrician, obstetrician, or internist) Board certification-yes or no AMA approved residency-yes or no f Certified family physician-yes or no * Non-certified family physician-yes or no t Certified specialist-yes or no Number of MDs in group Average number of patient visits per day MD age Length of practice in community Average number of personnel per MD 11. Patient and Disease Characteristics Infancy Age (of mother)

Education Social class Number of family members Number of children *Although both "Specialty status" and "Board certification" were used as independent variables, three additional independent variables defining four categories of physicians were also considered. These categories were: certified specialists, non-certified specialists, certified family physicians, and non-certified family physicians. The reason for including these subgroups of physicians was that in a previous analysis'3 certified family physicians were found to relate to patients in a different manner from the three other categories of

physicians.

I

Pregnancy Age Education Social class Number of family members Gravidity

Diabetes Mellitus Age Sex Education Social class Marital status Time with current MD Duration of disease Number of other conditions Insulin dependence

Congestive Heart Failure Age Sex Education Social class Marital status Time with current MD Duration of disease Number of other conditions Number of prior hospitalizations for CHF Most severe prior functional status

Quality Assurance in Patient Care Seminar Set

I

A seminar on the "State of the Art of Quality Assurance in Patient Care in the U.S." will be held September 20-21, 1976 at Case Western Reserve University, School of Medicine, Cleveland, Ohio. Session topics include: the role of government; the professional standards review organizations; theories and methods; actual medical audit experiences; the role of the computer; consumer interests; and thoughts on the future. Registration fee, including lunch both days, is $85. Direct inquiries to: William H. Kincaid, Assistant Professor, Dept. of Community Health, CWRU School of Medicine, Cleveland, OH 44106.

AJPH December, 1976, Vol. 66, No. 12

1179

Physician management in primary care.

Minimal explicit consensus criteria in the management of patients with four indicator conditions were established by an ad hoc committee of primary ca...
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