Development and first assessment of a questionnaire for health care utilization and costs for cardiac patients
© Schweikert et al; licensee BioMed Central Ltd. 2008
Received: 07 January 2008
Accepted: 19 September 2008
Published: 19 September 2008
The valid and reliable measurement of health service utilization, productivity losses and consequently total disease-related costs is a prerequisite for health services research and for health economic analysis. Although administrative data sources are usually considered to be the most accurate, their use is limited as some components of utilization are not systematically captured and, especially in decentralized health care systems, no single source exists for comprehensive utilization and cost data. The aim of this study was to develop and test a questionnaire for the measurement of disease-related costs for patients after an acute cardiac event (ACE).
To design the questionnaire, the literature was searched for contributions to the assessment of utilization of health care resources by patient-administered questionnaires. Based on these findings, we developed a retrospective questionnaire appropriate for the measurement of disease-related costs over a period of 3 months in ACE patients. Items were generated by reviewing existing guidelines and by interviewing medical specialists and patients. In this study, the questionnaire was tested on 106 patients, aging 35–65 who were admitted for rehabilitation after ACE. It was compared with prospectively measured data; selected items were compared with administrative data from sickness funds.
The questionnaire was accepted well (response rate = 88%), and respondents completed the questionnaire in an average time of 27 minutes. Concordance between retrospective and prospective data showed an intraclass correlation (ICC) ranging between 0.57 (cost of medical intake) and 0.9 (hospital days) with the other main items (physician visits, days off work, medication) clustering around 0.7. Comparison between self-reported and administrative data for days off work and hospitalized days were possible for n = 48. Respective ICCs ranged between 0.92 and 0.94, although differences in mean levels were observed.
The questionnaire was accepted favorably and correlated well with alternative measurement approaches. This first assessment showed promising characteristics of this questionnaire in different aspects of validity for patients with ACE. However, additional research and more extensive tests in other patient groups would be worthwhile.
The valid and reliable measurement of health service utilization, productivity losses and consequently total disease-related costs is a prerequisite for health economic analysis. While health effects can be measured by numerous generic and disease-specific instruments [1–3], much less work has been done regarding standardized methods to measure health care utilization and disease-specific costs.
Particularly when an economic evaluation is performed prospectively alongside a clinical trial, cost data may be collected by various methods, such as clinical records, insurance data, and data from health care providers. Patients may also provide data directly, by face to face interviews, retrospective cost questionnaires, and prospective cost diaries. Overall, health economic studies commonly use cost data from administrative data sources and routine databases from hospitals, health insurances, or health care providers. They are usually considered to be the most accurate method of cost measurement [4, 5]. However, the use of administrative data has some significant disadvantages. First, in economic evaluations adopting a societal perspective which includes all medical and non-medical costs and potential savings related to the disease studied is broadly recommended [6, 7]. Administrative data, however, will typically miss some cost components that should be considered. These include expenditures for over the counter drugs, travel expenses, or costs resulting from paid or unpaid informal care. These cost items are also essential if one is interested in the economic impact on patients by different types of treatment. Second, in decentralized health care systems, including many social security systems and market-oriented health systems, no single source exists for comprehensive cost data. When study patients are insured by multiple payers or receive their medical care at multiple sites, investigators must contact numerous third party payers and service providers in order to collect comprehensive cost data. In this case, the use of administrative data may not be feasible and may be inefficient even for a small number of patients. Thus in practice, investigators may rely to some degree on patient-reported data. However, this may lead to other problems typical of survey studies, such as non-response and missing data. Face to face interviews limit these problems but may be too costly for large numbers of patients . Diaries are considered to be feasible and valid, and are advantageous in that they do not rely on instantaneous recall . They allow information to be collected prospectively, which reduces the likelihood of recall error. However, once the diary is sent, it is impossible to determine whether the information was filled in promptly or after receiving reminder letters, which might be weeks later. While cost diaries are well accepted over the short term, significant problems have been reported over longer time periods, with drop-out rates of up to 50% of the study population over one year [8, 10, 11]. Similar problems arise with diaries for clinical trials and related health economic studies, where follow-up periods of 6–12 months are typical. In this case, a retrospective approach may be attractive. However, available retrospective instruments are rarely validated [9, 12]. To our knowledge, there is no tested instrument available that was designed to comprehensively measure the full range of direct and indirect medical and non-medical costs alongside a clinical trial in cardiac patients.
The aim of this study was to develop and test a patient-administered instrument for a clinical trial, which would allow comprehensive cost measurements related to cardiac disease over a longer time period without exceeding normal recall periods.
Thus, the objective of this article is (1) to introduce the instrument and its development, (2) to assess its acceptance and feasibility, and aspects of its validity in a clinical trial setting, (3) to identify the cost structure and the overall level of disease-related costs in patients after an acute cardiac event.
The cost questionnaire was designed as a booklet with instructions that allow the patients to complete it independently; it was based on the format and wording of cost diaries developed and introduced in studies of patients with low back pain  and inflammatory bowel disease .
An enclosed letter explained the study's aim and design and a telephone number was provided in case of questions. Patients were instructed at the beginning of the questionnaire to complete it alone. The cost items were adapted to the specific utilization pattern of cardiac patients after an acute event. These were based on published treatment guidelines and interviews with cardiac patients, cardiologists in private practice, and a physician at the rehabilitation clinic.
"Filter questions" were used for each cost item to clarify and to the improve user-friendliness of the questionnaire items. These asked whether any of the subsequent disease-related costs were incurred during the respective time frame. Only if the subject answered "yes" were they required to complete a subsequent table, in which frequency and/or cost of utilization were to be specified. In addition, the use of filter questions allowed "no" answers to be distinguished from missing answers, which is an important distinction when calculating mean costs.
A crucial issue in the development of the questionnaire was to determine the appropriate time frame for the single cost items based on literature regarding cognitive theory, empirical results in survey research, and a recent review in the field of health care . The following factors were identified and considered when determining the time frame and the framing of questions in order to balance underreporting due to recall error and potential overreporting due to so called "telescoping" effects. These are errors in reporting incurred by the temporal displacement of an event, which typically leads respondents to overreport utilization frequencies :
There is no single ideal time frame for the recall period of a cost questionnaire. The appropriate recall time span for different utilization variables differs with respect to the nature of cost items [17–21].
The less regularly an event occurs and the lower its subjective impact is, the less likely it is to be recalled exactly over the longer time frame .
Techniques of "bounded recall" should be used if possible . This means, that the time horizon is explicitly defined by exact dates and, for repeated measurements, the preceding answers and already recalled events should be shown.
The recall time frame of typical health care cost items should not exceed three to four months, although longer periods are possible for specific items depending on their salience (hospital admissions, long-term sick leave) [9, 18, 25, 26].
Closed questions should be used if possible in order to support the effects of recognition .
Cost components measure in cost questionnaire
Utilization of paid and unpaid help
Nature of help, duration (hours), outlays
Mean gross wage of a housekeeper
Type of transportation, number of rides, cost (if public transportation) or kilometers (car)
Outlays (public transportation), official schedule of travel expenses (car)
Physical activities, gym activities
Type of activity, average number per week, duration, outlays
Average prices per activity
Specialization of physician, number of consultations, services performed
Mean reimbursement per consultation
Intake of prescribed medication
Name of medication, current daily dosage, changes in medication or dosage
Official pharmaceutical price list
Intake of unprescribed medication
Name of medicine, number and size of packages purchased
Official pharmaceutical price list
Physical therapeutics/non-physician services
Type and number of services
Pricing schedule of statutory health insurance
Type and number of services, outlays
Outlays or price schedule of alternative care
Type of product, outlays/cost
Average market prices
Change in diet
Type of dietary changes, estimated additional outlays
Outlays estimated by patients
Lost productive time
Reason for lost productive time, duration
Average sex- and age-adjusted labor costs
Reason for inpatient treatment, duration
Average per diem rates**
Ingested medications were a mixed case. Recommended medications for heart disease are similar in the various guidelines, and their administration is typically regular and over the long term. Substitutions between various drugs within the same class may occur periodically [28–30]. Furthermore medication rates have generally been observed to remain quite stable after an ACE [31, 32]. However, changes in prescribed medications tend to be related to an acute event, which might be more important to the patient. This was resolved by asking the patient for their current daily intake. A subsequent question asked for changes in drug prescriptions occurring in the last three months. Correct recall was supported by "bounded recall" techniques. Thus, for the 3-month questionnaire, patients received a list with the discharge medications from cardiac rehabilitation.
The ordering of the questions was driven by the common recommendation in questionnaire design to start with rather easier questions e.g.  as well as the aim to avoid participants' confusion by switching between reference periods more often than needed. The questionnaire is available in its original German version as well as in an English translation which, however, has not been formally assessed [see Additional files 1 and 2].
Costs for medication and medical aids were valued using standard prices . Reported days off work and hospital days were multiplied by average labour costs and hospital costs respectively. All costs are inflation adjusted and presented in 2006 Euros.
The feasibility and acceptance of a cost questionnaire are crucial for its use in health economic studies. This is assessed by the response rate, which is defined as the proportion of returned questionnaires. As filter questions were used for each item, missing entries were defined as either missing information on the filter question itself or missing further information if the filter question was positively checked. Acceptance was also assessed by asking participants to rate the degree of difficulty of filling in the questionnaire on a four-point Likert scale.
Completeness and face validity
In order to determine the relevant resource categories related to cardiac problems, eight patients who underwent rehabilitation care after ACE were interviewed about their typical medical consumption and other disease-specific non-medical utilization. They were also asked to rate the relevance of the different cost items by themselves. This was used to differentiate between questions in a 4-week and 3-month recall period. Face validity of the questionnaire was then assessed by medical experts consisting of a physician at the rehabilitation hospital and two outpatient physicians. They judged the completeness and consistency of the questionnaire draft.
Convergent validity was tested by comparing the information provided by the questionnaire with an alternative collection method of patient reported data – a prospective cost diary – which was based on previously tested and reported instruments [5, 13]. Patients completed the cost diary prospectively over 4 weeks after cardiac rehabilitation. The information from the prospective cost diary was compared with the information from the retrospective questionnaire for an overlapping time period of 4 weeks. As some cost items were retrospectively assessed for the last 4 weeks (table 1), comparisons were possible for these cost items. Additional comparisons were possible by matching data which were asked in date format (hospital spells, spell off work), by reconstructing the retrospectively given history of medical intake, and by asking the patients in the tested questionnaire to assign the stated physician visits within the last 12 weeks to one of three 4 week spells after discharge from rehabilitation hospital.
For the cost items, days off work and hospital days, a third "objective" assessment was possible using administrative data from the statutory sickness funds which constitute the German public health insurance covering ~90% of the German general population. However, this analysis was only performed on a sub-sample, as some patients refused to allow the sickness fund the release of their data (n = 29), not all sickness funds responded to our request (n = 5), and some patients were privately insured (n = 11). Overall, the sickness funds provided information for 48 patients.
If patients consented, sickness funds were asked to list all sick leave and hospitalization days with the respective diagnoses codes during the 3 months after rehabilitation treatment (reference period). The validity of the questionnaire was assessed according to these data, which were considered to be the gold standard because sickness funds must pay sick benefits and hospital charges based on these data.
On admission to the rehabilitation hospital in southern Germany, 106 consecutive patients requiring rehabilitation (3–4 weeks) after an ACE were recruited. Exclusion criteria were (as in the subsequent clinical trial) age above 65 years, insufficient command of the German language, and an ACE occurring more than 3 months before admission to the rehabilitation hospital.
Patients received the prospective 4-week cost diary upon discharge from the rehabilitation hospital, while the 3-month retrospective cost questionnaire was mailed 3 months after discharge. Patients were instructed to complete the questionnaire by themselves.
If necessary, patients were mailed two reminders and, if they still did not return the questionnaire, they were telephoned. Participants also received a gift coupon of 12 € as an incentive after completing and returning the questionnaire. Monetary incentives have been shown to increase response rates for health questionnaires .
Internal consistency was tested using contingent tables with categorically scaled data. Intraclass correlation coefficients (ICC) between the prospective 4-week cost diary and the retrospective cost questionnaire were calculated from metrically scaled data, as this coefficient is a more suitable measure of agreement than, for example, Pearson correlation . To test validity, retrospective self-reports and administrative data were compared by t-test and intraclass correlation. Self-reported retrospective data and administrative data were also compared by plotting the differences between the values against the mean of the values in order to test for a relationship between the difference and the magnitude of the two values .
Calculations and statistical analysis were performed using the software package SAS 8.02 (SAS Institute Inc., Cary, NC, USA).
The study was approved by the Ethics Committee of the State Medical Chamber of Baden-Württemberg (Landesärztekammer). Informed written consent was obtained from each individual enrolled into the study.
Participant characteristics (n = 106)
Statutory health insurance
Private health insurance
Duration of disease since diagnosis (months)
Persons in household
Less than full time
Self-rated health 3 months after rehabilitation (VAS)
Feasibility and acceptability
The total response rate of the cost questionnaire was 88% (93/106). Sixty per cent (57) of the sample returned the questionnaire without an additional reminder. Roughly one-fifth (21) of respondents reacted after the first and another 14% (13) after the second reminder letter. Two participants only responded after being called. The 13 non-respondents were on average 4.8 years younger than the respondents (p = 0.04) and were more likely to be employed full time than respondents (60% vs. 77%).
The 20 filter questions, which had to be checked in each questionnaire, were used as an indicator of the degree of completion of the questionnaire. From the total of 1860 (20 × 93) questions to be answered by the 93 responders, 15 (0.8%) questions were not filled in. In addition the sequence accuracy after the filter question was assessed. In just two cases a positively checked filter question was not followed by a meaningful entry, whereas after all negatively checked questions the following detail table remained (rightly) blank.
Most of the respondents (92%) found the questionnaire easy or very easy to answer. Information on the average duration of completion was provided by 88 respondents. Time for completion was on average 27 minutes (standard deviation (SD) 25.6, ranging from 4 to 180 minutes, median 20). For 85% of the sample, completion of the questionnaire did not take more than 30 minutes.
Comparison of prospective cost diary and retrospective questionnaire for overlapping time (n = 90)*
Retrospective cost questionnaire
Number of physician visits
Days off work
Number of drugs
Cost of medical intake (€)
Cost of medical aids (€)
Comparison of medications measured by cost diary and retrospective questionnaire (n = 90)*
Medication (sales name)
Medication (generic name/agent)
Comparison of questionnaire and sickness fund data (n = 48)
Days off work hospitalized
Days off work not hospitalized
Total days of sick leave
Based on the full sample (n = 90), patients reported more sick leave in the questionnaire than in the diary. However, in the subpopulation for which sickness fund data were available (n = 48), subjects underreported sick leave days in the questionnaires over the 3-month period. Comparing the 4-week period covered by the available sickness fund data and the diary showed that the mean sick leave days agreed well between the diaries and the sickness fund data (17.1 vs. 17.6 days, p = 0.60), whereas there was slight underreporting of sick leave in the questionnaire (16.3 days, p = 0.24).
Health care and disease-related costs
Cost of care (for 3 months) based on retrospective data (n = 93)
Direct medical cost*
Additional cost for diet
Time off work for physician visits
Time off work
Health economic studies incorporating a societal perspective and performed alongside clinical trials must rely at least partially on patient-based information on resource consumption. This study's aim was to describe the development of a questionnaire measuring direct and indirect costs in patients after an acute cardiac event and to test its properties in terms of feasibility and aspects of validity.
The questionnaire was developed based on the results of survey research and cognitive psychology regarding the appropriate time frame of the cost items required to completely assess costs in an economic evaluation. In the development of this retrospective questionnaire, the major issues concerning the accuracy of utilization measurement, which were summarized recently by Bhandari and Wagner, were considered: the questionnaire was developed specifically for the sample population and their utilization patterns, recall aspects were taken into account, different forms of data collection were compared, and the instrument was finally revised with improved instructions . By explicitly describing the development process and the validation, we seek to contribute to the standardization of cost instruments and their standardized validation.
Acceptability and feasibility
The questionnaire was easy to use and showed a high response rate of 88%. The average completion time of 27 minutes is at the upper time limit acceptable to patients . As the median is considerably lower (20 minutes) and only 15% of subjects required more than 30 minutes for completion, the time burden was probably acceptable for most subjects. However, this could be a practical research problem if other patient-oriented outcomes are measured in addition to costs. As cost measurement showed that a substantial percentage of costs are due to just a few main cost drivers such as days off work, hospital admissions, and medications, it would be possible to reduce the number of cost items and related utilization questions without losing too much relevant information. However, this must be decided specifically for each study as there is a trade off between level of detail, accuracy and completeness versus acceptability.
The response pattern indicates the usefulness of reminders. Even the second reminder letter substantially raised the response rate whereas a third contact by telephone did not show a further significant improvement in participation. A third reminder letter is also probably useless because, by the time a third letter is sent, the likelihood of recall error and telescoping effects increases.
A problem in the study was the selection bias of responders. The age difference between responders and non-responders was 5 years, and the percentage of non-responders in full-time employment was substantially higher. Comparable studies on patient-reported utilization did not find differences in compliance with respect to age but with respect to marital status . The lower response rate of patients in full-time employment may be due to their tighter time schedule. Thus, the length of the questionnaire should be as short as possible, and the importance of continued response should be thoroughly explained to patients when motivating them to participate in the study. In clinical trials, results should be checked for an influence of full-time employment status.
Assessment of validity
Our comparison of the questionnaire with a patient diary and with data from sickness funds regarding some key variables supports its validity for cost measurement. The questionnaire agreed reasonably with the patient diary for variables that could be compared over the time period of 4 weeks. Comparison of medications showed that 61% agreed in terms of names and 81% agreed with respect to the active agent. Comparison of hospitalization, sick leave, and physician visits showed moderate to good correlation, although a significant difference in the level was observed. There was a tendency to underreporting compared with the prospective data and the administrative data, which has often been reported in studies analyzing retrospective patient-reported data compared with administrative or provider data [4, 5, 12, 37, 38].
In particular, the underreporting of sick leave and, therefore, indirect costs must be noted as this cost component is the dominant cost driver. This corresponds with other recent studies that have also found underreporting of lost productive time [9, 38]. One reason for this underreporting seems to be partly a lower response rate in patients who are active in the labor force. Therefore, measures aimed at increasing the response rate of working patients might lower the extent of underreporting in this important cost component.
A detailed analysis showed that the major difference in the mean value was effectively caused by single cases for which there was a great discrepancy between self-reported and administration data. It seemed that patients who were jobless at the time of the cost survey did not record sick leave although they were (correctly) listed in the sick leave data. Thus, describing this case in the instructions accompanying the questionnaire may increase agreement between the two sources.
Despite the good concordance indicated by measures of (linear) agreement, absolute utilization was mostly underreported when the results of the questionnaire were compared with administrative data and the diary. As this tendency does not appear to depend on baseline characteristics or health status, it seems unlikely that such deviations could bias the cost measurement of disease-related costs when differences between treatment groups are analyzed, as is usually the case in health economic evaluation studies.
As expected, the disease-related costs measured by this questionnaire are dominated by high indirect costs, which are known to be an important consequence of heart disease . The information on the distribution and variance in the data provides valuable information for statistical planning of health economic studies. Although the questionnaire has been developed to cover the typical utilization patterns of patients after an ACE, it could be adapted to other diseases, including layout and instructions, with minimal effort.
There were limitations of this study which need to be mentioned. As ACE has a high incidence in age groups over 65 years, the findings are not totally representative for the unrestricted population. No significant age-related differences were found in the quality of reporting in our study. This corresponds with the findings of Ritter et al., who did not detect any reporting differences according to demographic characteristics . Additional validation research focusing also on higher age classes would be of high interest.
The size of the study was planned to indicate whether the measurement approach was feasible and reasonably valid. For more detailed analysis, a larger study including a comparison with administrative data regarding medication and physician visits would be desirable. Due to various reasons, the comparison of the questionnaire with administrative data was just possible for n = 48 representing 45% of the starting sample of 106, which is a significant loss in power and might induce bias. The described selection process implies that for the n = 29 patients who did not sign the related patient agreement a systemic bias cannot be fully excluded, although there is no intuitive assumption as to how and for what reason the response pattern and agreement would systematically vary with the fact that the participants disagreed to contact. The information for the other cases n = 16 is in technical terms missing at random and therefore unlikely to introduce any bias for the results of the remaining sample.
As health care utilization is potentially subject to treatment variability, generalizability across countries cannot be taken for granted. In the case of secondary prevention after ACE, comparable treatment patterns are suggested across countries [28, 30], and thus the basic structure of potential utilization should be comparable between countries. Differences in resource availability and accessibility to health care systems will mainly impact the frequency of utilization (e.g. number of physician visits or special procedures in hospital), which can then be captured by the questionnaire.
The severity of the disease state may potentially have an impact on questionnaire acceptance. Considering the disease classification according to the New York Heart Association (NYHA) and self-rated health, the sample in this study was moderately affected by the consequences of their ACE. As there was only a weak correlation between measures of disease severity and questionnaire acceptance, this provides some evidence that the questionnaire can also be used in more severely affected populations as long as patients are cognitively and physically capable of completing the forms.
Also asking for information in overlapping periods might have had a positive impact on patients' commitment and their thoroughness in completing the questionnaire, resulting in higher acceptance and questionnaire agreement than in a non-clinical trial setting. This effect cannot be excluded for every research dealing with repeated measurements and might be dampened in this case by the fact that in most cases a time span of 8 weeks was in between the administration of the two instruments.
A final limitation of this questionnaire is that it is targeted on cardiac patients. It should be noted that before applying instruments to other areas of diseases a similar process of adaptation is recommended in order to capture the disease specific health care utilization. This process could include a literature review of main treatment patterns and examination and assessment of the draft instrument by medical experts as well as patients.
With the population under study the questionnaire was well accepted and showed good correlation with alternative measurement approaches. This preliminary assessment showed some promising characteristics of this questionnaire in different aspects of validity for patients with ACE and might present a possible alternative for the measurement of study costs in settings where the collection of administrative data is not feasible. However, additional research and more extensive tests would be worthwhile.
This study was supported by grants from the German Federal Ministry for Education and Research (01GD9820/0) and from German Pension Insurance (02708). The authors thank Gertrud Feike and Matthias Kurz for their support in the collection and handling of the data and Christian Becker for support in editing the manuscript.
- Patrick DL, Deyo RA: Generic and disease-specific measures in assessing health status and quality of life. Med Care. 1989, 27 (3 Suppl): S217-232. 10.1097/00005650-198903001-00018.View ArticlePubMedGoogle Scholar
- Bowling A: Measuring disease a review of disease specific quality of life measurement scales. 1995, Buckingham, Philadelphia: Open University PressGoogle Scholar
- Dempster M, Donnelly M: Measuring the health related quality of life of people with ischaemic heart disease. Heart. 2000, 83 (6): 641-644. 10.1136/heart.83.6.641.View ArticlePubMedPubMed CentralGoogle Scholar
- Ritter PL, Stewart AL, Kaymaz H, Sobel DS, Block DA, Lorig KR: Self-reports of health care utilization compared to provider records. J Clin Epidemiol. 2001, 54 (2): 136-141. 10.1016/S0895-4356(00)00261-4.View ArticlePubMedGoogle Scholar
- Goossens ME, Rutten-van Molken MP, Vlaeyen JW, Linden van der SM: The cost diary: a method to measure direct and indirect costs in cost- effectiveness research. J Clin Epidemiol. 2000, 53 (7): 688-695. 10.1016/S0895-4356(99)00177-8.View ArticlePubMedGoogle Scholar
- Weinstein MC, Siegel JE, Gold MR, Kamlet MS, Russell LB: Recommendations of the Panel on Cost-effectiveness in Health and Medicine. JAMA. 1996, 276 (15): 1253-1258. 10.1001/jama.276.15.1253.View ArticlePubMedGoogle Scholar
- Drummond MF, Stoddart GL, Torrance GW: Methods for the economic evaluation of health care programmes. 1997, Oxford: Oxford University Press, 2Google Scholar
- Verbrugge LM: Health diaries. Med Care. 1980, 18 (1): 73-95. 10.1097/00005650-198001000-00006.View ArticlePubMedGoogle Scholar
- Evans C, Crawford B: Patient self-reports in pharmacoeconomic studies. Their use and impact on study validity. Pharmacoeconomics. 1999, 15 (3): 241-256. 10.2165/00019053-199915030-00004.View ArticlePubMedGoogle Scholar
- Papke K, Janßen C: Tagebücher als Befragungsinstrument im Kontext des KORA-Projekts Krankheitskosten von Astma und Allergien. Z Gesundheitswiss. 2000, 8 (2): 149-157.View ArticleGoogle Scholar
- Fowler FJ: Improving survey questions: design and evaluation. 1995, Thousand Oaks: Sage PublicationsGoogle Scholar
- Petrou S, Murray L, Cooper P, Davidson LL: The accuracy of self-reported healthcare resource utilization in health economic studies. Int J Technol Assess Health Care. 2002, 18 (3): 705-710. 10.1017/S026646230200051X.View ArticlePubMedGoogle Scholar
- Becker A, Seitz R, Jacobi E, Leidl R: [Cost evaluation by a patient questionnaire: pilot study of a weekly cost diary](in German). Rehabilitation (Stuttg). 2001, 40 (1): 12-20.View ArticleGoogle Scholar
- Stark R, Konig HH, Leidl R: Costs of inflammatory bowel disease in Germany. Pharmacoeconomics. 2006, 24 (8): 797-814. 10.2165/00019053-200624080-00006.View ArticlePubMedGoogle Scholar
- Bhandari A, Wagner T: Self-reported utilization of health care services: improving measurement and accuracy. Med Care Res Rev. 2006, 63 (2): 217-235. 10.1177/1077558705285298.View ArticlePubMedGoogle Scholar
- Schwarz N, Sudman S: Answering questions: methodology for determining cognitive and communicative processes in survey research. 1996, San Francisco: Jossey-Bass Publishers, 1Google Scholar
- Loftus E, Smith K, Johnson D, Fiedler J: Remembering "when": Errors in the dating of autobiographical memories. Practical Aspects of Memory: Current Research and Issues Volume 1 Memory in Everyday Life. Edited by: Gruneberg M, Morris P, Sykes R. 1988, Chichester, New York, Brisbane, Toronto, Singapore: John Wiley & Sons, 234-240.Google Scholar
- Jobe JB, White AA, Kelley CL, Mingay DJ, Sanchez MJ, Loftus EF: Recall strategies and memory for health-care visits. Milbank Q. 1990, 68 (2): 171-189. 10.2307/3350095.View ArticlePubMedGoogle Scholar
- Means B, Loftus E: When personal history repeats itself: decomposing memories for recurring events. Applied Cognitive Psychology. 1991, 5: 297-318. 10.1002/acp.2350050402.View ArticleGoogle Scholar
- Shum MS, Rips LJ: The Respondents's Confession: Autobiographical Memory in the Context of Surveys. Cognition and survey research. Edited by: Sirken MG, Herrmann DJ, Schechter S, Schwarz N, Tanur JM, Tourangeau R. 1999, New York: Wiley, 95-109.Google Scholar
- Cannell CF, Marquis KH, Laurent A: A summary of studies of interviewing methodology. Vital Health Stat 1. 1977, Series 2 (69): i-viii, 1–78.Google Scholar
- Sudman S, Bradburn NM: Asking questions. 1982, San Francisco: Jossey-Bass, 1Google Scholar
- Sudman S, Bradburn NM, Schwarz N: Thinking about answers: the application of cognitive processes to survey methodology. 1996, San Francisco: Jossey-Bass Publishers, 1Google Scholar
- Durante R, Ainsworth BE: The recall of physical activity: using a cognitive model of the question-answering process. Med Sci Sports Exerc. 1996, 28 (10): 1282-1291.View ArticlePubMedGoogle Scholar
- Mauskopf J, Schulman K, Bell L, Glick H: A strategy for collecting pharmacoeconomic data during phase II/III clinical trials. Pharmacoeconomics. 1996, 9 (3): 264-277.View ArticlePubMedGoogle Scholar
- Johnston K, Buxton MJ, Jones DR, Fitzpatrick R: Assessing the costs of healthcare technologies in clinical trials. Health Technol Assess. 1999, 3 (6): 1-76.PubMedGoogle Scholar
- Converse JM, Presser S: Survey questions: Handcrafting the standardized questionnaire. 1986, Beverly Hills: Sage PublicationsView ArticleGoogle Scholar
- Swedberg K, Cleland J, Dargie H, Drexler H, Follath F, Komajda M, Tavazzi L, Smiseth OA, Gavazzi A, Haverich A, et al: Guidelines for the diagnosis and treatment of chronic heart failure: executive summary (update 2005): The Task Force for the Diagnosis and Treatment of Chronic Heart Failure of the European Society of Cardiology. Eur Heart J. 2005, 26 (11): 1115-1140. 10.1093/eurheartj/ehi204.View ArticlePubMedGoogle Scholar
- Goff DCr, Gu L, Cantley LK, Sheedy DJ, Cohen SJ: Quality of care for secondary prevention for patients with coronary heart disease: results of the Hastening the Effective Application of Research through Technology (HEART) trial. Am Heart J. 2003, 146 (6): 1045-1051. 10.1016/S0002-8703(03)00522-2.View ArticlePubMedGoogle Scholar
- Smith SC, Blair SN, Bonow RO, Brass LM, Cerqueira MD, Dracup K, Fuster V, Gotto A, Grundy SM, Miller NH, et al: AHA/ACC Scientific Statement: AHA/ACC guidelines for preventing heart attack and death in patients with atherosclerotic cardiovascular disease: 2001 update: A statement for healthcare professionals from the American Heart Association and the American College of Cardiology. Circulation. 2001, 104 (13): 1577-1579. 10.1161/hc3801.097475.View ArticlePubMedGoogle Scholar
- Willich SN, Muller-Nordhorn J, Kulig M, Binting S, Gohlke H, Hahmann H, Bestehorn K, Krobot K, Voller H: Cardiac risk factors, medication, and recurrent clinical events after acute coronary disease; a prospective cohort study. Eur Heart J. 2001, 22 (4): 307-313. 10.1053/euhj.2000.2294.View ArticlePubMedGoogle Scholar
- Yan AT, Tan M, Fitchett D, Chow CM, Fowlis RA, McAvinue TG, Roe MT, Peterson ED, Tu JV, Langer A, et al: One-year outcome of patients after acute coronary syndromes (from the Canadian Acute Coronary Syndromes Registry). Am J Cardiol. 2004, 94 (1): 25-29. 10.1016/j.amjcard.2004.03.024.View ArticlePubMedGoogle Scholar
- Krauth C, Hessel F, Hansmeier T, Wasem J, Seitz R, Schweikert B: [Empirical standard costs for health economic evaluation in Germany – a proposal by the working group methods in health economic evaluation] Article in German. Gesundheitswesen. 2005, 67 (10): 736-746. 10.1055/s-2005-858698.View ArticlePubMedGoogle Scholar
- Kenyon S, Pike K, Jones D, Taylor D, Salt A, Marlow N, Brocklehurst P: The effect of a monetary incentive on return of a postal health and development questionnaire: a randomised trial [ISRCTN53994660]. BMC Health Serv Res. 2005, 5: 55-10.1186/1472-6963-5-55.View ArticlePubMedPubMed CentralGoogle Scholar
- Bland JM, Altman DG: Statistical methods for assessing agreement between two methods of clinical measurement. Lancet. 1986, 1 (8476): 307-310.View ArticlePubMedGoogle Scholar
- Holm K: Die Befragung. 1975, München: Francke Verlag, 1Google Scholar
- Roberts RO, Bergstralh EJ, Schmidt L, Jacobsen SJ: Comparison of self-reported and medical record health care utilization measures. J Clin Epidemiol. 1996, 49 (9): 989-995. 10.1016/0895-4356(96)00143-6.View ArticlePubMedGoogle Scholar
- Merkesdal S, Ruof J, Huelsemann JL, Mittendorf T, Handelmann S, Mau W, Zeidler H: Indirect cost assessment in patients with rheumatoid arthritis (RA): comparison of data from the health economic patient questionnaire HEQ-RA and insurance claims data. Arthritis Rheum. 2005, 53 (2): 234-240. 10.1002/art.21080.View ArticlePubMedGoogle Scholar
- Luengo-Fernandez R, Leal J, Gray A, Petersen S, Rayner M: The cost of cardiovascular disease in the UK. Heart. 2006Google Scholar
- The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1472-6963/8/187/prepub