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Predictors of cost-effectiveness of selected COPD treatments in primary care: UNLOCK study protocol

Predictors of cost-effectiveness of selected COPD treatments in primary care: UNLOCK study protocol www.nature.com/npjpcrm All rights reserved 2055-1010/15 PROTOCOL OPEN Predictors of cost-effectiveness of selected COPD treatments in primary care: UNLOCK study protocol 1 2 3 4 1,5 3 Job FM van Boven , Miguel Román-Rodríguez , Janwillem WH Kocks , Joan B Soriano , Maarten J Postma and Thys van der Molen npj Primary Care Respiratory Medicine (2015) 25, 15051; doi:10.1038/npjpcrm.2015.51; published online 6 August 2015 BACKGROUND METHODS Chronic obstructive pulmonary disease (COPD) puts a high burden Study design 1,2 on patients and governmental health-care budgets. General This is a cost-effectiveness analysis that is performed with a real-world practitioners (GPs) have a pivotal role in the treatment of COPD database on respiratory patients. patients in primary care. However, the strategies of treatment may differ considerably between individual GPs, resulting in large intra- Setting individual differences in health-care utilisation and quality of life 3,4 This study comprises two phases, with the first phase including all primary of their patients. Recently, the Spanish AUDIPOC study showed care centres in the Balearic Islands, Spain. In a second phase of the study, great variability in hospital treatment patterns and patients’ primary care centres from other parts of the world will be included. outcomes. Moreover, the European COPD audit indicated marked differences in resources available across different hospitals in Europe. In Spain though, it is estimated that at least 61% of COPD Data source patients are only treated in primary care, with an average of 6.6 All the data will be extracted from the MAJOrca Real-world Investigation in visits per year. The estimated prevalence of COPD in the Balearic COPD and Asthma database (MAJORICA). The MAJORICA database Islands is 12.8%. Regarding health-care costs for respiratory contains combined data from the primary care system (e-SIAP), the patients, several cost drivers, mostly related to patient character- hospital claims system (FIC), and the pharmacy database (RELE) in the Balearics, Spain. Together, these databases cover all health-care utilisation istics, have been identified in previous studies including of the permanent inhabitants of the Balearics (±1.1 million subjects). In the associated comorbidities (e.g., heart disease), forced expiratory Balearics, there are about 400 different GPs, and most of the COPD patients volume in 1 s (FEV ), the physical component of quality of life, 6- are treated by one of these GPs. The MAJORICA database contains data min walking distance, increased dyspnoea, number of medical from all patients aged ⩾ 18 years with a primary care diagnosis of asthma 9–11 visits and hospitalisations. Although one study identified an and/or COPD in 2012, regardless of health insurance. All demographics, effect of the individual physician on health-care costs, treatment clinical data, diagnostic tests, as well as resource use, pharmacy dispense strategies were never incorporated as a predicting variable for data, work absence and patient-reported outcomes from almost 70,000 costs or outcomes. Besides inter-physician differences in treat- respiratory patients are available for the period 2011–2014. A specification ments, country-specific regulations and difference in the extent of of the database is provided in Table 1. The database characteristics were reported according to the checklists of the IPCRG and the Respiratory adherence to clinical guidelines may affect the cost-effectiveness Effectiveness Group (http://www.effectivenessevaluation.org). The unique of treating COPD patients in primary care settings. It was shown island setting of the Balearics allows us to provide an almost complete that adherence to COPD treatment guidelines is suboptimal. picture of the real-world health-care use of COPD patients. Moreover, non-adherence to guidelines was associated with higher total health-care costs. In particular, in times of increasing health-care costs and scarcer resources, there is a need to identify Inclusion criteria the cost-effectiveness of different treatment strategies for COPD All patients (⩾18 years) with a clinical diagnosis of COPD (ICD-9 codes: 491, patients across various primary care settings. The UNLOCK project 492, 496 and/or primary codes R79, R95) in 2012, available in the of the International Primary Care Respiratory Group (IPCRG) offers MAJORICA database, were included. In addition, patients needed to be a a promising possibility. permanent resident of the Balearic Islands and to be alive in 2014. Health-care resource utilisation AIMS Health-care resource use in 2013 and 2014 will be calculated for all the The primary aim of this study is to assess what makes one COPD COPD patients identified in 2012. Health-care resource use that will be treatment strategy more cost-effective than others, by taking into included in the study refers to the following: GP visits, primary care nurses account factors related to patients, the physician, and specific visits, emergency department (ED) visits, specialist visits, specialist nurse follow up and treatment approaches. A secondary objective is to visits, hospitalisations, medication and diagnostic tests (that is, spirometry, assess whether real-world cost-effectiveness of treatments is CT-scans, X-rays, bronchoscopy). To estimate indirect costs, data on work comparable between Spain and other countries that have absence will be extracted. These data will be extracted from the e-SIAP comparable data sets available. system, as work absence in Spain is registered by GPs. 1 2 Unit of PharmacoEpidemiology and PharmacoEconomics (PE2), Department of Pharmacy, University of Groningen, Groningen, The Netherlands; Institituto de Investigacíon Sanitaria de Palma (IdISPa), Palma de Mallorca, Spain; Department of General Practice, University Medical Centre Groningen, University of Groningen, Groningen, The 4 5 Netherlands; Instituto de Investigación Hospital Universitario de la Princesa (IISP), Universidad Autónonoma de Madrid, Cátedra UAM-Linde, Madrid, Spain and Institute of Science in Healthy Aging and HealthcaRE (SHARE), University Medical Centre Groningen, University of Groningen, Groningen, The Netherlands. Correspondence: M Román-Rodríguez (miguelroman@ibsalut.caib.es) Received 27 March 2015; revised 25 May 2015; accepted 10 June 2015 © 2015 Primary Care Respiratory Society UK/Macmillan Publishers Limited Cost-effectiveness of COPD treatment JFM van Boven et al Table 1. Specification of the MAJORICA database Table 1. (Continued ) Variable Specification Variable Specification Type of database Covariates Electronic Medical Record Yes Comorbidities Claims Yes Diabetes Yes Cardiovascular diseases Country/countries of data origin Balearics, Hypertension Yes Spain Cardiac insufficiency Number of patients 68,578 Atrial fibrillation Patients with asthma diagnosis (ICD-9: 493) 45,800 Cor pulmonale Patients with COPD diagnosis (ICD-9: 491, 492, 496) 27,871 Allergic rhinitis Yes Patients with asthma and COPD diagnosis (ICD-9: 5,093 Cerebrovascular disease Yes 493 and (491. 492, 496)) Osteoporosis Yes Data collection (period) 2011–2014 Sleep apnoea Yes Unique identifier/anonymisation Yes Nasal polyps No Ethical approval Yes Depression/anxiety Yes Reflux (GERD) Yes Coding system diseases Chronic kidney disease Yes ICD-9, ICD-10, read ICD-9 Lung Cancer Yes AIDS/HIV Yes Patient demographics Cognitive dysfunction No Gender Yes Risk score Age Yes Cardiovascular risk score Yes BMI Yes Lifestyle Smoking status Yes Physician demographics Smoking years Yes Gender Yes Socioeconomic status Age Yes Post code No Setting (urban/rural) Yes Education level No Employment status Yes Drugs Salary range No Coding ATC-7 Spirometry Prescribed, dispensed, both Dispensed FEV /FVC, FEV %pred, reversibility Yes 1 1 Drugs available All R03 Laboratory tests Dose/dosing Yes Full blood count, FeNO, IgE and so on No Device No Imaging OTC medications No CRX Performed Y/N Inhaler technique No HRCT Performed Y/N Abbreviations: ACT, asthma control test; ATC, anatomical therapeutic Vaccinations chemical; BMI, body mass index; CAT, COPD Assessment Test; CRX, chest Influenza, Pneumococcal Yes X-ray; FEV, forced expiratory volume; FVC, forced vital capacity; GERD, gastroesophageal reflux disease; HRCT, high-resolution computed tomo- Outcomes graphy; ICD, International Classification of Diseases; ICU, intensive care Exacerbations unit; mMRC, modified Medical Research Council; N, no; OTC, over the Steroids Yes counter; SABA, short-acting beta agonists; Y, yes. Antibiotics Yes SABA Yes Exacerbations (ICD-9 code) Yes Health resource utilisation Calculation of health-care costs and indirect costs Primary care consultations Yes Total costs will be calculated by multiplying each unit of resource use and Secondary care consultations Yes lost workdays with standard cost-per-unit prices, which are obtained from Consultations coded by disease Yes the Health Care Administration Office of the Balearics. Consultations coded by routine/emergency Yes Hospitalisations Yes Hospitalisations coded by disease Yes Predictors for cost-effectiveness Hospitalisation duration Yes Predictors for cost-effective treatment will be assessed, including variables Emergency room Yes related to patient, physician or treatment. Predictors related to patients ICU Yes may include age, gender, body mass index, smoking status, exacerbations ICU coded by disease Yes (physician diagnosis and/or prescription of prednisone), COPD severity by ICU duration Yes spirometry, short-acting β -agonist use, health-related quality of life and Rehabilitation No 2 comorbidity. Examples of predictors related to the physician are age, Physiotherapy No gender and setting, number of patients per practice and number of COPD Patient-reported mMRC Yes patients per practice. Predictors related to treatment may include Asthma (ACQ, ACT) ACT score prescription of medication and adherence based on refill of medication, COPD (CCQ, CAT) CAT score influenza vaccination in the past year, requests for diagnostic tests, Side effects referrals to hospital or specialists and the use of patient-reported outcomes Pneumonias Yes (PROs). Work absence All cause Yes Comparisons Respiratory specificYes Specifications of the comparisons that could potentially be made, depending on the exact data available, are listed in Table 2. npj Primary Care Respiratory Medicine (2015) 15051 © 2015 Primary Care Respiratory Society UK/Macmillan Publishers Limited Cost-effectiveness of COPD treatment JFM van Boven et al Data analysis others) to participate to test the external validity and inter-country variation of these predictors. The total patients’ sample will be split into two groups, depending on the To assure consistency of the analytic process and consequent results, treatment variables that will be compared (Table 2). For example, to assess data will be compared with other data sets from different IPCRG countries, the impact of using PROs, all patients who were treated by a GP who uses including the same variables and applying the same methods. PROs will be selected as the treatment group. An equal group of control patients, not treated by a GP who uses PROs, will be selected using a matching procedure. The matching procedure (based on propensity Ethical approval scores) will use patient characteristics (age, gender, smoking status) and Ethical approval was granted by the local primary care research committee. disease severity (FEV , exacerbations, quality of life, comorbidities). For both groups, the average total costs per patient (as well as minimum, maximum and standard deviation) will be calculated on the basis of the DISCUSSION direct health-care costs, as listed above (hospitalisations, medication, ED Current clinical treatment guidelines are mainly based on evidence visits), and indirect costs. The cost difference between the two groups will from large clinical trials with a selective study population, which result in a ΔC variable to obtain an estimate of the incremental costs. The differences in effect size (ΔE) will be expressed as the difference in health does not seem to reflect the majority of patients treated in real- 18,19 effects between the two groups that are compared. The health effects world primary care. Therefore, there is an urgent need to assess depend on what variables will be consistently available in the database. the validity of treatment recommendations when applied in real- Exacerbations avoided will be used, as well as changes in COPD-specific world treatment. Results from this study are expected to provide changes in the quality of life, as defined by the COPD Assessment Test (CAT) useful insights in the cost-effectiveness of the broad range of or modified Medical Research Council (mMRC) questionnaire. strategies and factors related to the primary care treatment of Subsequently, the incremental cost-effectiveness ratio (ICER) can be COPD. The use of a real-world database that covers the complete calculated as follows: (Costs − Costs )− (Effects − Effects )= group1 group2 group1 group2 Balearic population is considered a major strength, as a represen- ΔC/ΔE, which provides the incremental costs per exacerbation avoided or tative population is assessed in which the risk of pre-selection bias incremental costs per CAT point gained. The ICER will be calculated using both is limited. A second strength is that results will be compared with the health-care payer’s and the societal perspective. The societal perspective other international settings, thereby increasing generalisability. includes work productivity costs. Sensitivity analyses will be performed using the minimal and maximal costs (scenario analyses), as well as a Here, the UNLOCK project of IPCRG offers a useful possibility. bootstrap procedure (as patient-level data will be available). Bootstrapping However, given the retrospective observational design, some relies on random sampling with replacement, and it will allow estimating limitations should be acknowledged. First, by the use of real- accuracy (such as 95% confidence intervals) to sample estimates. world data, missing data are common. In particular, registration of data regarding the use of spirometry, smoking status and patient- External validity using UNLOCK reported outcomes is expected to be limited. Pulmonary rehabilita- tion and physiotherapy data are not included in the effectiveness Once the predictors have been identified, we will invite members of the UNLOCK project in other countries (e.g., The Netherlands, Sweden and analysis because of the difficulty in collecting such data and because of the limited availability of these services. In addition, miscoding or incomplete and invalid data collection may have Table 2. Comparison of cost-effectiveness to be potentially made occurred because of the real-word setting. Another limitation lies in between groups the observational design, which usually increases the risk for bias. Although the database itself covers the complete population, the Predictors related to patient individual analyses are prone to selection bias. To minimise this risk Age o75 years 75 years or more Gender Male Female of bias, a matching procedure will be used, but unobserved bias BMI o25 25 or more may still occur. Despite these limitations, the need for more real- Smoking status Current smoker Former smoker or world evidence and comparative effectiveness research is increas- non-smoker ing, thereby strengthening the overall relevance of this study. Exacerbations o2 2 or more Hospitalisations 0 1 or more Severity by FEV o50% 50% or more COMPETING INTERESTS Use of SABA o2 dispenses per 2 or more JWHK and JBS are Associate Editors of npj Primary Care Respiratory Medicine, but were year not involved in the editorial review of, nor the decision to publish, this article. None Comorbidity o2 2 or more of the other authors declare any conflict of interest. Cardiovascular No Yes HRQoL CATo10 10 or more GP visits o2 2 or more FUNDING Medication adherence o80% 80% or more This study is funded by an UNLOCK study grant of the International Primary Care Predictors related to GP Respiratory Group (IPCRG) and co-funded by an unrestricted educational grant from Age o35 35 years or older GlaxoSmithKline (GSK). Gender Male Female Region Urban Rural Use of PROs Yes No REFERENCES Requests for lab/tests Yes No 1 World Health Organization. Chronic obstructive pulmonary disease. Available at http://www.who.int/respiratory/copd/en/. Accessed 22 February 2015. Predictors related to specific treatment 2 van Boven JF, Vegter S, van der Molen T, Postma MJ. COPD in the working age Influenza vaccination Yes No population: the economic impact on both patients and government. COPD 2013; LABA Yes No 10: 629–639. LAMA Yes No 3 Lababidi H, Abu-Shaheen AK, Bou Mehdi IA, Al-Tannir MA. Asthma care practicing LABA-ICS Yes No among general practitioners in Lebanon: a cross-sectional study. J Asthma 2014; 51:51–57. Abbreviations: BMI, body mass index; CAT, COPD Assessment Test; GP, general 4 de Miguel-Diez J, Carrasco-Garrido P, Rejas-Gutierrez J, Martin-Centeno A, practitioner; HRQoL, health-related quality of life; ICS, inhaled corticosteroid; Gobartt-Vazquez E, Hernandez-Barrera V et al. Inappropriate overuse of inhaled LABA, long-acting β -agonist; LAMA, long-acting muscarinic antagonist; PROs, corticosteroids for COPD patients: impact on health costs and health status. Lung patient-reported outcomes; SABA, short-acting β -agonist. 2011; 189: 199–206. © 2015 Primary Care Respiratory Society UK/Macmillan Publishers Limited npj Primary Care Respiratory Medicine (2015) 15051 Cost-effectiveness of COPD treatment JFM van Boven et al 5 Pozo-Rodriguez F, Lopez-Campos JL, Alvarez-Martinez CJ, Castro-Acosta A, 14 Perez X, Wisnivesky JP, Lurslurchachai L, Kleinman LC, Kronish IM. Barriers to Aguero R, Hueto J et al. Clinical audit of COPD patients requiring hospital adherence to COPD guidelines among primary care providers. Respir Med 2012; admissions in Spain: AUDIPOC study. PLoS One 2012; 7: e42156. 106:374–381. 6 Lopez-Campos JL, Hartl S, Pozo-Rodriguez F, Roberts CM. European COPD Audit 15 Miravitlles M, Sicras A, Crespo C, Cuesta M, Brosa M, Galera J et al. Costs of chronic team. Variability of hospital resources for acute care of COPD patients: the Eur- obstructive pulmonary disease in relation to compliance with guidelines: a study opean COPD Audit. Eur Respir J 2014; 43:754–762. in the primary care setting. Ther Adv Respir Dis 2013; 7: 139–150. 7 Izquierdo-Alonso JL, de Miguel-Diez J. Economic impact of pulmonary drugs 16 Chavannes N, Stallberg B, Lisspers K, Roman M, Moran A, Langhammer A et al. on direct costs of stable chronic obstructive pulmonary disease. COPD 2004; 1: UNLOCK: Uncovering and Noting Long-term Outcomes in COPD to enhance 215–223. knowledge. Prim Care Respir J 2010; 19: 408. 8 Soriano JB, Yanez A, Renom F, de la Pena M, Gomez A, Duro R et al. Set-up and 17 Official Bulletin of the Balearic Islands. Available at http://boib.caib.es/pdf/2012040/ pilot of a population cohort for the study of the natural history of COPD and OSA: mp63.pdf. Accessed 20 February 2015. the PULSAIB study. Prim Care Respir J 2010; 19:140–147. 18 Herland K, Akselsen JP, Skjonsberg OH, Bjermer L. How representative are clinical 9 de Miguel Diez J, Carrasco Garrido P, Garcia Carballo M, Gil de Miguel A, Rejas study patients with asthma or COPD for a larger "real life" population of patients Gutierrez J, Bellon Cano JM et al. Determinants and predictors of the cost of COPD with obstructive lung disease? Respir Med 2005; 99:11–19. in primary care: a Spanish perspective. Int J Chron Obstruct Pulmon Dis 2008; 3: 19 Kruis AL, Stallberg B, Jones RC, Tsiligianni IG, Lisspers K, van der Molen T et al. 701–712. Primary care COPD patients compared with large pharmaceutically-sponsored 10 Mapel DW, McMillan GP, Frost FJ, Hurley JS, Picchi MA, Lydick E et al. Predicting COPD studies: an UNLOCK validation study. PLoS One 2014; 9: e90145. the costs of managing patients with chronic obstructive pulmonary disease. 20 Conway PH, Clancy C. Comparative-effectiveness research—implications of the Respir Med 2005; 99:1325–1333. Federal Coordinating Council’s report. N Engl J Med 2009; 361:328–330. 11 Garcia-Polo C, Alcazar-Navarrete B, Ruiz-Iturriaga LA, Herrejon A, Ros-Lucas JA, Garcia-Sidro P et al. Factors associated with high healthcare resource utilisation among COPD patients. Respir Med 2012; 106: 1734–1742. This work is licensed under a Creative Commons Attribution 4.0 12 Verdaguer Munujos A, Peiro S, Librero J. Variations in the use of hospital resources International License. The images or other third party material in this in treating patients with chronic obstructive pulmonary disease. Arch Bronco- article are included in the article’s Creative Commons license, unless indicated neumol 2003; 39: 442–448. otherwise in the credit line; if the material is not included under the Creative Commons 13 Sharif R, Cuevas CR, Wang Y, Arora M, Sharma G. Guideline adherence in man- license, users will need to obtain permission from the license holder to reproduce the agement of stable chronic obstructive pulmonary disease. Respir Med 2013; 107: material. To view a copy of this license, visit http://creativecommons.org/licenses/ 1046–1052. by/4.0/ npj Primary Care Respiratory Medicine (2015) 15051 © 2015 Primary Care Respiratory Society UK/Macmillan Publishers Limited http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png npj Primary Care Respiratory Medicine Springer Journals

Predictors of cost-effectiveness of selected COPD treatments in primary care: UNLOCK study protocol

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Springer Journals
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Copyright © 2015 by The Author(s)
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Medicine & Public Health; Medicine/Public Health, general; Primary Care Medicine; Internal Medicine; Pneumology/Respiratory System; Thoracic Surgery
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www.nature.com/npjpcrm All rights reserved 2055-1010/15 PROTOCOL OPEN Predictors of cost-effectiveness of selected COPD treatments in primary care: UNLOCK study protocol 1 2 3 4 1,5 3 Job FM van Boven , Miguel Román-Rodríguez , Janwillem WH Kocks , Joan B Soriano , Maarten J Postma and Thys van der Molen npj Primary Care Respiratory Medicine (2015) 25, 15051; doi:10.1038/npjpcrm.2015.51; published online 6 August 2015 BACKGROUND METHODS Chronic obstructive pulmonary disease (COPD) puts a high burden Study design 1,2 on patients and governmental health-care budgets. General This is a cost-effectiveness analysis that is performed with a real-world practitioners (GPs) have a pivotal role in the treatment of COPD database on respiratory patients. patients in primary care. However, the strategies of treatment may differ considerably between individual GPs, resulting in large intra- Setting individual differences in health-care utilisation and quality of life 3,4 This study comprises two phases, with the first phase including all primary of their patients. Recently, the Spanish AUDIPOC study showed care centres in the Balearic Islands, Spain. In a second phase of the study, great variability in hospital treatment patterns and patients’ primary care centres from other parts of the world will be included. outcomes. Moreover, the European COPD audit indicated marked differences in resources available across different hospitals in Europe. In Spain though, it is estimated that at least 61% of COPD Data source patients are only treated in primary care, with an average of 6.6 All the data will be extracted from the MAJOrca Real-world Investigation in visits per year. The estimated prevalence of COPD in the Balearic COPD and Asthma database (MAJORICA). The MAJORICA database Islands is 12.8%. Regarding health-care costs for respiratory contains combined data from the primary care system (e-SIAP), the patients, several cost drivers, mostly related to patient character- hospital claims system (FIC), and the pharmacy database (RELE) in the Balearics, Spain. Together, these databases cover all health-care utilisation istics, have been identified in previous studies including of the permanent inhabitants of the Balearics (±1.1 million subjects). In the associated comorbidities (e.g., heart disease), forced expiratory Balearics, there are about 400 different GPs, and most of the COPD patients volume in 1 s (FEV ), the physical component of quality of life, 6- are treated by one of these GPs. The MAJORICA database contains data min walking distance, increased dyspnoea, number of medical from all patients aged ⩾ 18 years with a primary care diagnosis of asthma 9–11 visits and hospitalisations. Although one study identified an and/or COPD in 2012, regardless of health insurance. All demographics, effect of the individual physician on health-care costs, treatment clinical data, diagnostic tests, as well as resource use, pharmacy dispense strategies were never incorporated as a predicting variable for data, work absence and patient-reported outcomes from almost 70,000 costs or outcomes. Besides inter-physician differences in treat- respiratory patients are available for the period 2011–2014. A specification ments, country-specific regulations and difference in the extent of of the database is provided in Table 1. The database characteristics were reported according to the checklists of the IPCRG and the Respiratory adherence to clinical guidelines may affect the cost-effectiveness Effectiveness Group (http://www.effectivenessevaluation.org). The unique of treating COPD patients in primary care settings. It was shown island setting of the Balearics allows us to provide an almost complete that adherence to COPD treatment guidelines is suboptimal. picture of the real-world health-care use of COPD patients. Moreover, non-adherence to guidelines was associated with higher total health-care costs. In particular, in times of increasing health-care costs and scarcer resources, there is a need to identify Inclusion criteria the cost-effectiveness of different treatment strategies for COPD All patients (⩾18 years) with a clinical diagnosis of COPD (ICD-9 codes: 491, patients across various primary care settings. The UNLOCK project 492, 496 and/or primary codes R79, R95) in 2012, available in the of the International Primary Care Respiratory Group (IPCRG) offers MAJORICA database, were included. In addition, patients needed to be a a promising possibility. permanent resident of the Balearic Islands and to be alive in 2014. Health-care resource utilisation AIMS Health-care resource use in 2013 and 2014 will be calculated for all the The primary aim of this study is to assess what makes one COPD COPD patients identified in 2012. Health-care resource use that will be treatment strategy more cost-effective than others, by taking into included in the study refers to the following: GP visits, primary care nurses account factors related to patients, the physician, and specific visits, emergency department (ED) visits, specialist visits, specialist nurse follow up and treatment approaches. A secondary objective is to visits, hospitalisations, medication and diagnostic tests (that is, spirometry, assess whether real-world cost-effectiveness of treatments is CT-scans, X-rays, bronchoscopy). To estimate indirect costs, data on work comparable between Spain and other countries that have absence will be extracted. These data will be extracted from the e-SIAP comparable data sets available. system, as work absence in Spain is registered by GPs. 1 2 Unit of PharmacoEpidemiology and PharmacoEconomics (PE2), Department of Pharmacy, University of Groningen, Groningen, The Netherlands; Institituto de Investigacíon Sanitaria de Palma (IdISPa), Palma de Mallorca, Spain; Department of General Practice, University Medical Centre Groningen, University of Groningen, Groningen, The 4 5 Netherlands; Instituto de Investigación Hospital Universitario de la Princesa (IISP), Universidad Autónonoma de Madrid, Cátedra UAM-Linde, Madrid, Spain and Institute of Science in Healthy Aging and HealthcaRE (SHARE), University Medical Centre Groningen, University of Groningen, Groningen, The Netherlands. Correspondence: M Román-Rodríguez (miguelroman@ibsalut.caib.es) Received 27 March 2015; revised 25 May 2015; accepted 10 June 2015 © 2015 Primary Care Respiratory Society UK/Macmillan Publishers Limited Cost-effectiveness of COPD treatment JFM van Boven et al Table 1. Specification of the MAJORICA database Table 1. (Continued ) Variable Specification Variable Specification Type of database Covariates Electronic Medical Record Yes Comorbidities Claims Yes Diabetes Yes Cardiovascular diseases Country/countries of data origin Balearics, Hypertension Yes Spain Cardiac insufficiency Number of patients 68,578 Atrial fibrillation Patients with asthma diagnosis (ICD-9: 493) 45,800 Cor pulmonale Patients with COPD diagnosis (ICD-9: 491, 492, 496) 27,871 Allergic rhinitis Yes Patients with asthma and COPD diagnosis (ICD-9: 5,093 Cerebrovascular disease Yes 493 and (491. 492, 496)) Osteoporosis Yes Data collection (period) 2011–2014 Sleep apnoea Yes Unique identifier/anonymisation Yes Nasal polyps No Ethical approval Yes Depression/anxiety Yes Reflux (GERD) Yes Coding system diseases Chronic kidney disease Yes ICD-9, ICD-10, read ICD-9 Lung Cancer Yes AIDS/HIV Yes Patient demographics Cognitive dysfunction No Gender Yes Risk score Age Yes Cardiovascular risk score Yes BMI Yes Lifestyle Smoking status Yes Physician demographics Smoking years Yes Gender Yes Socioeconomic status Age Yes Post code No Setting (urban/rural) Yes Education level No Employment status Yes Drugs Salary range No Coding ATC-7 Spirometry Prescribed, dispensed, both Dispensed FEV /FVC, FEV %pred, reversibility Yes 1 1 Drugs available All R03 Laboratory tests Dose/dosing Yes Full blood count, FeNO, IgE and so on No Device No Imaging OTC medications No CRX Performed Y/N Inhaler technique No HRCT Performed Y/N Abbreviations: ACT, asthma control test; ATC, anatomical therapeutic Vaccinations chemical; BMI, body mass index; CAT, COPD Assessment Test; CRX, chest Influenza, Pneumococcal Yes X-ray; FEV, forced expiratory volume; FVC, forced vital capacity; GERD, gastroesophageal reflux disease; HRCT, high-resolution computed tomo- Outcomes graphy; ICD, International Classification of Diseases; ICU, intensive care Exacerbations unit; mMRC, modified Medical Research Council; N, no; OTC, over the Steroids Yes counter; SABA, short-acting beta agonists; Y, yes. Antibiotics Yes SABA Yes Exacerbations (ICD-9 code) Yes Health resource utilisation Calculation of health-care costs and indirect costs Primary care consultations Yes Total costs will be calculated by multiplying each unit of resource use and Secondary care consultations Yes lost workdays with standard cost-per-unit prices, which are obtained from Consultations coded by disease Yes the Health Care Administration Office of the Balearics. Consultations coded by routine/emergency Yes Hospitalisations Yes Hospitalisations coded by disease Yes Predictors for cost-effectiveness Hospitalisation duration Yes Predictors for cost-effective treatment will be assessed, including variables Emergency room Yes related to patient, physician or treatment. Predictors related to patients ICU Yes may include age, gender, body mass index, smoking status, exacerbations ICU coded by disease Yes (physician diagnosis and/or prescription of prednisone), COPD severity by ICU duration Yes spirometry, short-acting β -agonist use, health-related quality of life and Rehabilitation No 2 comorbidity. Examples of predictors related to the physician are age, Physiotherapy No gender and setting, number of patients per practice and number of COPD Patient-reported mMRC Yes patients per practice. Predictors related to treatment may include Asthma (ACQ, ACT) ACT score prescription of medication and adherence based on refill of medication, COPD (CCQ, CAT) CAT score influenza vaccination in the past year, requests for diagnostic tests, Side effects referrals to hospital or specialists and the use of patient-reported outcomes Pneumonias Yes (PROs). Work absence All cause Yes Comparisons Respiratory specificYes Specifications of the comparisons that could potentially be made, depending on the exact data available, are listed in Table 2. npj Primary Care Respiratory Medicine (2015) 15051 © 2015 Primary Care Respiratory Society UK/Macmillan Publishers Limited Cost-effectiveness of COPD treatment JFM van Boven et al Data analysis others) to participate to test the external validity and inter-country variation of these predictors. The total patients’ sample will be split into two groups, depending on the To assure consistency of the analytic process and consequent results, treatment variables that will be compared (Table 2). For example, to assess data will be compared with other data sets from different IPCRG countries, the impact of using PROs, all patients who were treated by a GP who uses including the same variables and applying the same methods. PROs will be selected as the treatment group. An equal group of control patients, not treated by a GP who uses PROs, will be selected using a matching procedure. The matching procedure (based on propensity Ethical approval scores) will use patient characteristics (age, gender, smoking status) and Ethical approval was granted by the local primary care research committee. disease severity (FEV , exacerbations, quality of life, comorbidities). For both groups, the average total costs per patient (as well as minimum, maximum and standard deviation) will be calculated on the basis of the DISCUSSION direct health-care costs, as listed above (hospitalisations, medication, ED Current clinical treatment guidelines are mainly based on evidence visits), and indirect costs. The cost difference between the two groups will from large clinical trials with a selective study population, which result in a ΔC variable to obtain an estimate of the incremental costs. The differences in effect size (ΔE) will be expressed as the difference in health does not seem to reflect the majority of patients treated in real- 18,19 effects between the two groups that are compared. The health effects world primary care. Therefore, there is an urgent need to assess depend on what variables will be consistently available in the database. the validity of treatment recommendations when applied in real- Exacerbations avoided will be used, as well as changes in COPD-specific world treatment. Results from this study are expected to provide changes in the quality of life, as defined by the COPD Assessment Test (CAT) useful insights in the cost-effectiveness of the broad range of or modified Medical Research Council (mMRC) questionnaire. strategies and factors related to the primary care treatment of Subsequently, the incremental cost-effectiveness ratio (ICER) can be COPD. The use of a real-world database that covers the complete calculated as follows: (Costs − Costs )− (Effects − Effects )= group1 group2 group1 group2 Balearic population is considered a major strength, as a represen- ΔC/ΔE, which provides the incremental costs per exacerbation avoided or tative population is assessed in which the risk of pre-selection bias incremental costs per CAT point gained. The ICER will be calculated using both is limited. A second strength is that results will be compared with the health-care payer’s and the societal perspective. The societal perspective other international settings, thereby increasing generalisability. includes work productivity costs. Sensitivity analyses will be performed using the minimal and maximal costs (scenario analyses), as well as a Here, the UNLOCK project of IPCRG offers a useful possibility. bootstrap procedure (as patient-level data will be available). Bootstrapping However, given the retrospective observational design, some relies on random sampling with replacement, and it will allow estimating limitations should be acknowledged. First, by the use of real- accuracy (such as 95% confidence intervals) to sample estimates. world data, missing data are common. In particular, registration of data regarding the use of spirometry, smoking status and patient- External validity using UNLOCK reported outcomes is expected to be limited. Pulmonary rehabilita- tion and physiotherapy data are not included in the effectiveness Once the predictors have been identified, we will invite members of the UNLOCK project in other countries (e.g., The Netherlands, Sweden and analysis because of the difficulty in collecting such data and because of the limited availability of these services. In addition, miscoding or incomplete and invalid data collection may have Table 2. Comparison of cost-effectiveness to be potentially made occurred because of the real-word setting. Another limitation lies in between groups the observational design, which usually increases the risk for bias. Although the database itself covers the complete population, the Predictors related to patient individual analyses are prone to selection bias. To minimise this risk Age o75 years 75 years or more Gender Male Female of bias, a matching procedure will be used, but unobserved bias BMI o25 25 or more may still occur. Despite these limitations, the need for more real- Smoking status Current smoker Former smoker or world evidence and comparative effectiveness research is increas- non-smoker ing, thereby strengthening the overall relevance of this study. Exacerbations o2 2 or more Hospitalisations 0 1 or more Severity by FEV o50% 50% or more COMPETING INTERESTS Use of SABA o2 dispenses per 2 or more JWHK and JBS are Associate Editors of npj Primary Care Respiratory Medicine, but were year not involved in the editorial review of, nor the decision to publish, this article. None Comorbidity o2 2 or more of the other authors declare any conflict of interest. Cardiovascular No Yes HRQoL CATo10 10 or more GP visits o2 2 or more FUNDING Medication adherence o80% 80% or more This study is funded by an UNLOCK study grant of the International Primary Care Predictors related to GP Respiratory Group (IPCRG) and co-funded by an unrestricted educational grant from Age o35 35 years or older GlaxoSmithKline (GSK). Gender Male Female Region Urban Rural Use of PROs Yes No REFERENCES Requests for lab/tests Yes No 1 World Health Organization. Chronic obstructive pulmonary disease. Available at http://www.who.int/respiratory/copd/en/. 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Respir Med 2013; 107: material. To view a copy of this license, visit http://creativecommons.org/licenses/ 1046–1052. by/4.0/ npj Primary Care Respiratory Medicine (2015) 15051 © 2015 Primary Care Respiratory Society UK/Macmillan Publishers Limited

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Published: Aug 6, 2015

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