Table 1 Characteristics of included studies looking at factors affecting the uptake of new medicines
From: Barriers and facilitators to the uptake of new medicines into clinical practice: a systematic review
Author(s), publication year, country | Study objective related to this systematic review | Study Design | Data Source | Setting | Medicine(s) | Sample | Key Findings | Funding source and Conflict of interest (COI) |
|---|---|---|---|---|---|---|---|---|
Abraham et al. (2010), USA [21] | To investigate if participation in clinical trials research network influences adoption of alcohol pharmacotherapies in publicly funded programs | Quantitative | Face-to-face interviews and brief telephone interviews | Primary and secondary care | acamprosate | 244 public programs, 127 Clinical Trail Network (CTN) affiliated program administrators | Affiliation of programs with CTN; Percentage of master’s level counsellors; Access to a prescribing physician. | Funding: national funding body COI: not reported |
AbuDagga et al. (2014), USA [22] | To identify factors associated with dabigatran versus warfarin use | Quantitative | Administrative pharmacy and medical claims database | Primary and secondary care | dabigatran | 20,320 patients | Patient’s clinical and demographic characteristics; Speciality of prescriber; Patient’s health insurance plan type. | Funding: Daiichi Sankyo COI: one author was employee of Daiichi Sankyo; another received payments from Daiichi Sankyo; four authors-none |
Anderson et al. (2015), USA [23] | To determine if conflict of interest policies influence psychiatrists’ antipsychotic prescribing and compare prescribing between academic and non-academic psychiatrists | Quantitative | IMS Health databases and physicians’ characteristics database | Primary and secondary care | Nine new and reformulated antipsychotics | 2464 prescribers | Affiliation with academic medical centres with conflict-of-interest policies; Type of prescriber (academic or non-academic). | Funding: national funding body COI: none |
Anderson et al. (2018), USA [24] | To explore characteristics of prescribers adopting new cardiovascular medicines | Quantitative | IMS Health databases | Primary and secondary care | dabigatran, aliskiren | 5953 physicians | Speciality of prescriber; Gender of prescriber; Medical school attended by prescriber. | Funding: national funding body COI: none |
Baik et al. (2016), USA [25] | To evaluate how patient characteristics are associated with the initiation of anticoagulant for patients newly diagnosed with atrial fibrillation | Quantitative | Pharmacy claims database | Primary and secondary care | dabigatran, rivaroxaban | 17,193 patients | Patient clinical and demographic characteristics; Patient’s health insurance plan type; Out-of-pocket expenses- no effect. | Funding: national funding body COI: none |
Boon et al. (2008), Belgium [26] | To examine the impact of reimbursement restrictions on the choice of antiepileptic (AEDs) medicines | Quantitative | Structured face-to-face interviews | Secondary care | 16 AEDs, including old and new | 100 neurologists | Reimbursement condition; Formulary restrictions. | Funding: GlaxoSmithKline COI: not reported |
Bourke and Roper (2012), UK [27] | To explore the factors that shape the timing of the first prescription of six new medicines by General Practitioners (GPs) | Quantitative | Prescribing and GP characteristics databases | Primary care | escitalopram, rofecoxib, esomeprazole, desloratadine, nicotine, drospirenone and oestrogen | 625 GP practices | Availability of nurse or clerical support; Participation in national incentive program to reduce prescribing costs; Previous early adoption of new medicines; GP’s prescribing portfolio size; Geographical location of GP practice. | Funding: not reported COI: not reported |
Brais et al. (2017), Canada [28] | To identify predictors of oral anticoagulant choice for patients with atrial fibrillation | Quantitative | Electronic medical records | Secondary care | dabigatran, rivaroxaban, apixaban | 439 patients at single teaching hospital | Patient’s demographic and clinical characteristics; Speciality of prescriber. | Funding: Bayer Inc., and Bristol-Myers Squibb Company-Pfizer alliance COI: not reported |
Burden et al. (2015), Canada [29] | To examine the impact of formulary changes to the use of zoledronic acid | Quantitative | Pharmacy claim database and prescriber databases | Primary and secondary care | zolendronic acid, denosumab | 18,226 patients | Formulary status change (removal of prior authorisation); Speciality of prescriber; Gender of prescriber. | Funding: national funding body COI: none |
Carracedo-MartÃnez et al. (2017), Spain [30] | To assess the impact of the removal of prior authorization requirements for two coxibs on their use | Quantitative | Pharmacy claim database | Primary care | celecoxib, etoricoxib | One health district,catchment area of 383,125 people | Formulary prescribing conditions (prior authorisation requirement). | Funding: none COI: none |
Chamberlain et al. (2014), UK [31] | To explore the impact of the Cancer Drug Fund (CDF) on access to cancer medicines in England, compared with Wales | Quantitative | IMS Health databases | Secondary care | 15 cancer medicines | Not stated- prescribing volumes milligrams/1000 population used | The CDF was associated with higher prescription volumes in England for most medicines, which NICE had rejected for some or all indications pre-CDF and for medicines, which NICE had not appraised pre-CDF, but subsequently rejected. | Funding: national funding body COI: none |
Chitagunta et al. (2009), USA [32] | To study the role of learning in the diffusion of three Cox-2 Inhibitors before withdrawal of rofecoxib | Quantitative | Prescription and advertising expenditure databases, published articles | Primary and secondary care | celecoxib, rofecoxib, valdecoxib | 6577 patients and 17,329 prescriptions | Advertising, news and academic articles; Socio-economic status of patient; Patient’s demographic characteristics; Patient’s health insurance plan type; Patient’s satisfaction with existing treatment. | Funding: not reported COI: not reported |
Chressanthis et al. (2012), USA [33] | To examine the effect of access limits to pharmaceutical representatives on new medicines prescribing by physicians | Quantitative | IMS Health databases | Primary and secondary care | sitagliptin | 65,131 physicians | Organisation restrictions to pharmaceutical representative access; Speciality and age of prescriber; Size and geographical location of organisation | Funding: AstraZeneca COI: two authors were employees of AstraZeneca |
Conti et al. (2012), USA [34] | To examines how evidence of the incremental effectiveness of novel chemotherapy medicines impacts on the adoption by physicians | Quantitative | Chemotherapy order system database | Secondary care | Seven oral chemotherapy medicines | 4,344,711 patients, 122 medical oncology practices in 35 the USA states | Severity of the underlying disease; Clinical trials and media reports concurrent with market launch date; Medicine effectiveness. | Funding: national funding body COI: not reported |
DeVore et al. (2018), USA [35] | To identified patient, provider, and practice characteristics associated with sacubitril/valsartan use | Quantitative | Observations | Primary and secondary care | sacubitril/valsartan | 4216 patients, 121 sites across the USA | Patient’s clinical and demographic characteristics; Socio-economic status of patient; Patient’s health insurance plan type; Speciality of prescriber; Size of organisation; Staff composition at the organisation. | Funding: Novartis COI: five authors in previous receipt of funding from pharmaceutical industry; two acts as consultants to pharmaceutical industry; two were employees of Novartis |
Donohue et al. (2018), USA [36] | To estimate the effect of peer adoption of three first-in-class medications on physicians’ own adoption of those medications. | Quantitative | IMS Health, insurance, and administrative claims databases | Primary and secondary care | dabigatran, sitigliptin, aliskiren | 11,958 physicians | Peer influence (internal and external). | Funding: national funding body COI: not reported |
Ducharme and Abraham (2008), USA [37] | To examine predictors of buprenorphine adoption | Quantitative | Brief telephone interviews and survey database | Primary and secondary care | buprenorphine | Staff members from 49 USA states and a data set of 12,236 substance abuse treatment facilities | Government owned and non-profit facilities; Hospital-based programs and opioid treatment programs; Programs offering detoxification services; Accredited programmes; Programmes serving adult population; Geographical location and size of programme; Government funding; Programs having at least one managed care contract; Coverage of medicine by patient’s health insurance. | Funding: national funding body COI: none |
Dybdahl et al. (2011), Denmark [38] | To analyse associations between GPs’ clinical interests and their preference for new medicine | Quantitative | Postal survey and pharmacy prescription database | Primary care | Three COX-2 inhibitors and six angiotensin-II antagonists medicines | 68 GPs | Continuous medical education activities. | Funding: not reported COI: authors received consultant fees or/and were previously involved in pharmaceutical industry funded research |
Friedman et al. (2010), USA [39] | To examine the influence of senior managers’ characteristics on the adoption of buprenorphine | Quantitative | Telephone survey | Primary and secondary care | buprenorphine | 547 pairs of administrative directors and clinical supervisors | Gender, age, the length of service and views of programme directors on treatment; Affiliations and accreditation of programme; Breadth of provided medical services and use of other medicines; Staff composition; Gender of patients. | Funding: national funding body COI: |
Fuksa et al. (2015), Czech Republic [40] | To evaluate the overall changes in statin utilisation and expenditure with regards to the changing prescribing conditions | Quantitative | Insurance prescription claims database | Primary and secondary care | atorvastatin, rosuvastatin | 774,281 patients | Changes in formulary prescribing conditions. | Funding: not reported COI: not reported |
Garjon et al. (2012), Spain [41] | To analyse the diffusion of new medicines during the first months of use and examine the adoption between family physicians and specialists | Quantitative | Prescription database | Primary and secondary care | cefditoren, duloxetine, etoricoxib, ezetimibe, levocetirizine, olmesartan, pregabalin and tiotropium | 1248 physicians | Speciality of prescriber; Therapeutic innovation of medicine; Range of indications for medicine; Prior authorisation requirement. | Funding: not reported COI: three authors received educational fees from pharmaceutical industry |
Groves et al. (2010), Canada [42] | To assess relationship between physicians’ characteristics and prescribing of new medicines | Quantitative | Administrative and insurance claims databases | Primary and secondary care | Four COX-2 inhibitors and two non-selective NSAIDs medicines | 925 physicians | Demographic characteristics; Speciality of prescriber; Geographical location of practice; Caseload of prescriber. | Funding: not reported COI: not declared |
Haider et al. (2008), Sweden [43] | To examine the association between educational level of patients and the use of newly marketed medicines among elderly patients | Quantitative | Three national registers: prescribed medicines, inpatient, and education | Primary and secondary care | 18 newly marketed medicines with at least 350 users | 626,258 patients | Patient’s educational level and gender; Number of prescribed medicines for patient; Patient’s residential area. | Funding: not reported COI: none |
Hickson et al. (2019), USA [44] | To describe trends over time in the initiation of the dipeptidyl peptidase-4 (DPP-4) inhibitors before and after removal of the rosiglitazone black box warning and restricted access program | Quantitative | Administrative claims database | Primary and secondary care | DPP-4 inhibitors | 280,969 patients | Regulatory restrictions to the use of medicines in the same category as new medicines. | Funding: not reported COI: one author was employee of Truven Health Analytics/IBM Watson Health |
Hirunrassamee and Ratanawijitrasin (2009), Thailand [45] | To assess access to medicines and other medical technologies under the three government health insurance schemes | Quantitative | Hospital electronic database and paper records | Secondary care | Antiepileptic and antineoplastic lung cancer medicines | 913 patients (antiepileptics), 33 patients (antineoplastics); 3 hospital sites | Patient’s health insurance plan type; Out-of-pocket payments. | Funding: not reported COI: not reported |
Hsieh and Liu (2012), Taiwan [46] | To explore issues surrounding utilisation of biologics in Taiwan | Quantitative | National insurance claims database | Secondary care | trastuzumab, rituximab, peginterferon-alfa-2A, etanercept | 590 patients | Size of hospital; Type of hospital ownership; Patient’s clinical characteristics. | Funding: national funding body, Johnson & Johnson COI: none |
Huang et al. (2013), USA [47] | To examine factors that influence doctors’ decision in initiating or switching from warfarin to dabigatran | Quantitative | Online survey | Secondary care | dabigatran | 65 physicians | Cost of medicine; Patient’s socioeconomic status; Patient’s clinical characteristics; Speciality of prescriber; Experience of prescriber with the medicine; Perceived benefits of new over ‘old’ therapy. | Funding: not reported COI: not reported |
Huskamp et al. (2013), USA [48] | To examined physician adoption of second-generation antipsychotic medications and identified physician-level factors associated with early adoption | Quantitative | IMS Health prescription database | Primary and secondary care | olanzapine, quetiapine, ziprasidone, and aripiprazole | 30,369 physicians | Age and gender of prescriber; Speciality of prescriber; Size and type of practice; Caseload of prescriber; Medical school location of prescriber. | Funding: national funding body COI: one author consulted National Railways Labor Conference |
Iyengar et al. (2011), USA [49] | To assess the impact of social networks on the adoption of a new medicine by physicians | Quantitative | Mailed and online survey, IMS Health databases, and pharmaceutical company sales calls records | Primary and secondary care | A newly launched prescription medicine used to treat a specific type of viral infection (short and long-term) | 185 physicians from three cities | Peers influence- the level of impact is shaped by peer’s usage volume and by the clinicians’ perception of their self-reported opinion leadership. Perceived leaders by colleagues adopted new medicine quicker than self-reported leaders. | Funding: not reported COI: not reported |
Karampli et al. (2020), Greece [50] | To explore factors influencing adoption of new antidiabetic medicines for patients with type 2 diabetes mellitus | Qualitative | Semi-structured face-to-face interviews | Primary and secondary care | DDP-4 inhibitors, GLP-1 agonists, SGLT2 inhibitors, new oral fixed-dose combinations of glycose-lowering medications, new dosage forms | 10 physicians | New medicine’s safety profile, efficacy, degree of relative advantage, formulation, cost, ease of use; Habitual prescribing of physician; Physician’s needs and values of practice; Physician’s experience with established medicines; Patient’s clinical and demographic characteristics; Patient’s preferences and adherence to treatment; Patient’s health insurance plan type; Working place of physician. | Funding: none COI: none |
Keating et al. (2018), USA [51] | To examine diffusion of bevacizumab and assess variation in use across oncology practices | Quantitative | Insurance claim database | Secondary care | bevacizumab | 2329 practices | Size and accreditation of organisation; Staff composition at organisation; Patient’s clinical and demographic characteristics; Patient’s socio-economic status. | Funding: national funding body COI: none |
Keating et al. (2020), USA [52] | To understand adoption of bevacizumab by oncologists for patients with cancer using network analysis method | Quantitative | Insurance claim database | Secondary care | bevacizumab | 44,012 patients, 3261physicians, 51 hospital referral regions | Patient’s clinical and demographic characteristics; Age of prescriber; Peer influence. | Funding: national funding body COI: one author received consultant fees from Grail |
Kennedy et al. (2020), Ireland [53] | To compare the use of direct oral anticoagulants in areas with warfarin clinics compared to those without | Quantitative | Pharmacy claims database shapefiles of warfarin clinics and areas | Primary care | apixaban, dabigatran, edoxaban, rivaroxaban | Â | Presence or absence of hospital-based warfarin clinics- no effect. | Funding: national funding body COI: none |
Kereszturi et al. (2015), Hungary [54] | To identify socio-demographic, workplace, practice, prescribing and patient characteristics of the early prescribers of the newly marketed innovative medicines | Quantitative | DoktorInfo prescription database | Secondary care | vildagliptin with metformin and metformin with sitagliptin combinations | 318 physicians | Portfolio width and prescribing volume of prescriber; Number of patients looked after by prescriber and number of consultations per patient; Prescribing of other branded medicines; Proportion of patients treated with insulin. | Funding: AXA Research Fund COI: not reported |
King et al. (2013), USA [55] | To examine the effect of attending a medical school with an active policy on restricting gifts from representatives of pharmaceutical and device industries on subsequent prescribing behaviour | Quantitative | IMS Health database and physicians’ characteristics database | Primary care | lisdexamfetamine, paliperidone, desvenlafaxine | 8602 physicians | Attending a medical school with an active gift restriction policy; Length of exposure to gift restriction policy. | Funding: national funding body COI: none |
King and Bearman (2017), USA [56] | To examine how different pharmaceutical detailing regulations and peer influence shaped medicine diffusion processes of newly marketed medicines | Quantitative | IMS Health prescription database | Primary care | lisdexamfetamine, duloxetine | 208,072 physicians for duloxetine, 215,445 physicians for lis-dexamfetamine | Policies limiting or banning gifts from pharmaceutical industry; Peer influence. | Funding: not reported COI: not reported |
Knudsen et al. (2009), USA [57] | To examines the adoption of buprenorphine over a 2-year period in community-based treatment programs associated and not with Clinical Trials Network (CTN) | Quantitative | Telephone and face-to-face interviews | Primary care | buprenorphine | 193 community-based treatment programs (CTPs) | Involvement in CTN buprenorphine protocol development; Size of organisation; Access to prescribers; Offering other inpatient services; Type of organisation. | Funding: national funding body COI: not reported |
Lin H et al. (2011), USA [58] | To explore the patterns of physician prescribing and medication choice for major depressive disorder between 1993 and 2007 | Quantitative | National survey database | Primary care | Four antidepressant drug classes | 125,605,444 patients | Patient’s health insurance type; Age of patient; Practice geographical location | Funding: not reported COI: not reported |
Lin S et al. (2011), Taiwan [59] | To examine how the prescribing decisions made by psychiatrists’ colleagues influence the likelihood of the psychiatrists’ initial prescription | Quantitative | National insurance database | Secondary care | duloxetine | 155 psychiatrists | Speciality of prescriber; Clinical experience of prescriber; Adoption behaviour of colleagues. | Funding: university funding COI: not reported |
Liu et al. (2011), Taiwan [60] | To investigate the effect of various economic factors on the diffusion of new medicines | Quantitative | National drug claims database | Primary and secondary care | seven oral anti-glycaemic medicines | 3,384,223 prescriptions | Degree of competition in the pharmaceutical and health service market; Size of the provide; Type of organisation; Disease severity; Geographical location of organisation. | Funding: national funding body COI: not reported |
Liu and Gupta (2012), USA [61] | To analyze individual physicians’ adoption of a newly launched prescription medicine | Quantitative | ImpactRx market research database and TNS Media Intelligence data (journal advertising expenditure) | Primary and secondary care | A newly launched medicine from one of the largest therapeutic classes of prescription medicines in USA, novel mechanism of action | 2129 physicians | Targeted detailing, journal advertising, meetings and events sponsored by industry, peer influence, and patient requests has positive impact. Specialists and prescribers with larger prescription volumes in the studied therapeutic class and who practice in communities with a larger percentage of patients from a White background adopted the new medicine quicker. | Funding: not reported COI: not reported |
Lo-Ciganic et al. (2016), USA [62] | To examine the physician adoption of dabigratran | Quantitative | IMS Health database and physicians’ characteristics database | Primary and secondary care | dabigatran | 3911 prescribers | Speciality of prescriber; Prescribers age; Hospital referral region; Patient’s health insurance plan type. | Funding: national funding body; university funding COI: none |
Luo et al. (2017), USA [63] | To assess the prevalence and variation in sacubitril/valsartan prescription among a real-world population with heart failure with reduced ejection fraction | Quantitative | National registry of hospitalised patients | Secondary care | sacubitril/valsartan | 21,078 patients, 241 hospital sites | Geographical location of organisation; Accreditation of organisation-no effect; Patient’s clinical and demographic characteristics; Patient’s health insurance plan type-no effect. | Funding: Novartis COI: one author was employee and three received consultant fees from Novartis; one received research funding from pharmaceutical companies |
Luo et al. (2018), USA [64] | To evaluate the early impact of this national treatment guideline update on the use of sacubitril/valsartan | Quantitative | National registry of hospitalised patients and national hospitals survey database | Secondary care | sacubitril/valsartan | 7200 patients | Size, location, accreditation of organisation and available services- no effect; National guideline publication- little/no effect. | Funding: Novartis COI: one author was employee of Novartis; four received research support from industry |
Luo et al. (2019), USA [65] | To identify hospital characteristics associated with the use of sacubitril/valsartan | Quantitative | National registry of hospitalised patients; national hospitals survey database, US census region, insurance claim database. | Secondary care | sacubitril/valsartan | 16,674 patients, 210 hospital sites | Size and accreditation of organisation-no effect; Organisation type (profit/non-profit); Geographical location of organisation; Follow-up ambulatory services-no effect. | Funding: Novartis COI: one author was employee of Novartis; three authors received research support from pharmaceutical companies |
Manchanda et al. (2008), USA [66] | To explore impact of marketing and interpersonal communication on the adoption of a new medicine in two unrelated markets | Mixed-methods | Pharmacy audit database, pharmaceutical company marketing records, interviews | Primary and secondary care | A new medicine from important medicine category | 466 physicians | Pharmaceutical industry targeted communication; Detailing, detailing stock, and sampling stock by pharmaceutical industry; Peer influence; Direct advertising to patients-no effect. | Funding: university funding COI: not reported |
Martin et al. (2017), France [67] | To explore the barriers to the diffusion of newly released oral targeted therapies dedicated to metastatic breast cancer | Qualitative | Semi-structured face-to-face interviews | Secondary care | everolimus | 40 physicians | Amount of new information to be acquired about the medicine; Lack of organisation in patient management; Time required to manage oral cancer treatments; Prescriber’s prescribing habits; No clear position of the new medicine in the therapeutic strategy; Being the only oncologist or multi-organ oncologist in the organisation. | Funding: Odyssea association COI: none |
Murphy et al. (2018), Ireland [68] | To explore factors that influence general practitioners prescribing of direct oral anticoagulants | Quantitative | Postal survey | Primary care | apixaban, dabigatran, edoxaban, rivaroxaban | 221 general practitioners | Hospital colleagues’ influence; Local and national guidelines; Conferences and journal articles; Clinical and demographic characteristics of patient; Perceived efficacy of medicine; Monitoring requirements; Size of practice. | Funding: none COI: none |
Netherland et al. (2009), USA [69] | To examine factors affecting willingness to adopt buprenorphine by physicians | Quantitative | On-site and online surveys | Primary care | buprenorphine | 172 prescribers, two national programs | Training of clinical staff on new medicine; Access to other services and treatments; Presence of effective referral system for alternative treatment; Adequate time per visit; Patients’ concerns about medicine; Availability of clinical guidelines and medicine; Reimbursement for consultation; Record keeping requirements; Access to an expert prescriber; Gender and ethnicity of prescriber; Experience and speciality of prescriber. | Funding: national funding body COI: not reported |
Ohl et al. (2013), USA [70] | To determine rural-urban variation in adoption of raltegravir amongst in national Veterans Affairs healthcare | Quantitative | Health care and residence databases | Primary and secondary care | raltegravir | 1222 patients | Residential area of patient; Patient’s clinical and demographic characteristics; Previous use of antiretroviral medicines. | Funding: national funding body COI: not reported |
Ohlsson et al. (2009), Sweden [71] | To investigate determinants of early adoption of rosuvastatin | Quantitative | National drug register | Primary care | rosuvastatin | 73,547 prescriptions from 170 health care practices | Type of ownership; Existence of strong therapeutic traditions; Socioeconomic status of patient. | Funding: not reported COI: not reported |
Patel et al. (2015), USA [72] | To characterise the prevalence, patterns, and predictors of direct oral anticoagulants versus warfarin therapy at discharge among atrial fibrillation patients hospitalised with ischemic stroke or transient ischemic attack | Quantitative | National stroke database | Secondary care | dabigatran, rivaroxaban | 61,655 patients from 1542 hospitals | Patient’s clinical characteristics; Ambulatory status of patient; Discharge destination; Patient’s health insurance plan type. | Funding: national funding body COI: two authors received consultant fees and three research support from pharmaceutical industries |
Potpara et al. (2017), Balkan countries [73] | To explore the use of direct oral anticoagulants in seven Balkan countries | Quantitative | Online survey | Secondary care | dabigatran, rivaroxaban, apixaban | 2663 patients from 49 centres | Speciality of prescriber; Patient’s clinical characteristics; Atrial fibrillation treatment strategy; Hospital-based centres; Previous use of oral anticoagulants. | Funding: none COI: six authors received speaker fees and one consultant fees from pharmaceutical industry |
Rodwin et al. (2020), USA [74] | To examine patient and hospital-level factors associated with prasugrel and ticagrelor use in acute myocardial infarction | Quantitative | National hospital registry for patients with myocardial infarction | Secondary care | prasugrel, ticagrelor | 362,354 patients, 801 hospitals | Patient’s clinical and demographic characteristics; Patient’s health insurance plan type; Number of patients treated in hospital; Geographical location and accreditation of organisation; Speed of adoption of previous innovation. | Funding: national funding body COI: one author received consultant fees and research support for pharmaceutical industry; one author received salary support from the funding body, funding from insurance companies, and hold equity interest in Medtronic |
Sato et al. (2012), Japan [75] | To assess the impact of the sitagliptin regulatory safety alert on the prescribing behaviour | Quantitative | Prescription data from 300 pharmacies | Primary and secondary care | sitagliptin | 87,678 patients | Size of hospital; Speciality of prescriber; Safety alert. | Funding: none COI: two authors received research support from pharmaceutical industry |
Savage et al. (2012), USA [76] | To examine the extent to which programs’ interorganisational institutional and resource-based linkages predict the likelihood of being an earlier adopter, later adopter, or non-adopter of buprenorphine | Quantitative | Face-to-face interviews and brief telephone interviews | Primary and secondary care | buprenorphine | 345 privately funded substance abuse treatment programs | Membership in national and regional associations; Detailing activities by pharmaceutical companies; Use of National Institute on Drug Abuse website as an information source. | Funding: national funding body COI: not reported |
Scholten et al. (2015), Germany [77] | To examine the factors at the organisational level that influence the implementation of systemic thrombolysis in stroke patients. | Quantitative | Hospital structure quality reports registry | Secondary care | alteplase | 286 hospitals | Existence of stroke unit; Hospital size. | Funding: none COI: none |
Steinberg et al. (2013), USA [78] | To identify patient and/or provider factors associated with the use of dabigatran in patients with atrial fibrillation | Quantitative | National registry for outpatients with atrial fibrillation | Secondary care | dabigatran | 8794 patients, 176 sites | Patient’s clinical and demographic characteristics; Patient’s health insurance plan type; Education level of patient; Current antiarrhythmic use; Speciality of prescriber. | Funding: Janssen Scientific Affairs, national funding body COI: seven author received consultant fees, five research support, two speaker fees from pharmaceutical industry, one author employed by Johnson & Johnson. |
Tanislav et al. (2018), Germany [79] | To investigate oral anticoagulation in stroke patients documented in a nationwide registry | Quantitative | National hospital quality registry | Secondary care | apixaban, dabigatran, edoxaban, rivaroxaban | 3813 patients | Treatment on stroke unit; Patient’s clinical and demographic characteristics; Previous oral anticoagulant/ antiplatelet use. | Funding: none COI: none |
Tobin et al. (2008), Australia [80] | To identify the factors that influence prescribing of new medicines among general practitioners, endocrinologists and psychiatrists | Qualitative | Focus groups with semi-structure interview guide | Primary and secondary care | Medicine that has in the past 1–2 years been in Pharmaceutical Benefit Scheme (PBS) listed, or released to the market, or a new chemical entity | 21 prescribers | Socioeconomic status of patient; Clinical need for medicine; New medicine’s attributes: adverse effects, safety, efficacy; Listing of medicine in PBS; Peer influence; Prescriber’s familiarity with the therapeutic area; Prescriber’s knowledge of the medicine. | Funding: non-profit organisation COI: not reported |
Tsai et al. (2010), Taiwan [81] | To examine factors affecting thiazolidinediones penetration into Taiwan’s hospitals | Quantitative | National health insurance database | Secondary care | pioglitazone, rosiglitazone | 580 hospitals | Degree of competition in the pharmaceutical market; Type of hospital; Type of ownership of hospital; Geographical location of hospital; Cost of medicines; Prescribing volume of diabetic medicines by hospital. | Funding: national funding body COI: not reported |
Wang et al. (2010), Taiwan [82] | To determine if socioeconomic status impacts adoption of newly reimbursed non-steroidal anti-inflammatory medicines under a universal health insurance program | Quantitative | Eight different electronic databases | Primary and secondary care | rofecoxib, celexocib, nimesultide | 875 patients | Patient’s clinical and demographic characteristics; Patient’s socio-economic status; Patient’s habits of health-care utilisation. | Funding: not reported COI: not reported |
Weir et al. (2012), Canada [83] | To explore the impacts of formulary listing changes and regulatory agency warnings on the use of erythropoiesis-stimulating agents in cancer patients | Quantitative | Prescription and physician characteristics databases, province people registry | Secondary care | Three erythropoiesis-stimulating agents | 171,967 patients | Formulary changes in reducing or removing restrictions for use; Safety warnings from regulatory agencies. | Funding: national funding body COI: one author received honorarium from Amgen |
Wen et al. (2011), Taiwan [84] | To characterise how a new medicine class for diabetes mellitus diffused in the health care market | Quantitative | National insurance claim database | Secondary care | rosiglitazone, pioglitazone | 580 hospitals | Accreditation and type of hospital; Type of ownership of hospital; Degree of competition in the pharmaceutical market; Geographical location of hospital; Number of prescribers prescribing these medicines; Prior anti-diabetic prescription capacity. | Funding: national funding body COI: none |
Zhang et al. (2019), Australia [85] | To evaluate how physicians’ risk preferences and personality affects their decisions to adopt new prescription medicines | Quantitative | Database of national panel survey of medical practitioners, insurance claim database | Primary care | apixaban, dabigatran, rivaroxaban | 576 GPs | Socio-demographic characteristics of prescriber; Prescribing volume; Willingness to take clinical risks; Employment status in the GP practice; Time spent in consultations; Location of GP practice; GP practice affiliations and social practice characteristics-no effect; Patient’s demographic characteristics; Patient’s socio-economic status. | Funding: national funding body, university COI: none |
Zhang et al. (2020), China [86] | To obtain information on the use of PD-1/PD-L1 inhibitors by oncologists in China | Quantitative | Online and offline survey | Secondary care | PD-1/PD-L1 checkpoint inhibitors | 588 oncologists | Knowledge and understanding mechanism of action of new medicines; Experience in using new medicines; New medicine’s attributes: cost, efficacy, adverse effects. | Funding: none COI: none |