Table 3.
Overview and general characteristics of included studies
| Authors (year) | Context (country/setting) | Study design | Type of prescribing | Comparator | Medicine management or prescribing activity | Study population |
| Black et al (2022)7 | UK, urban sexual health services | Mixed-methods and a comparative case study (cost–consequence framework) | Nurse IP | PGD by non-prescribing nurses | Prescribed medications | N=26 nurse prescribers N=67 PGDs users |
| Carey et al (2020)20 | UK, mixed range of settings (primary and secondary care, social enterprise and private practice) | Mixed-methods and a comparative case study (cost–consequence framework) | Physiotherapist IP Podiatrist IP |
Non-prescribing physiotherapists Non-prescribing podiatrists |
Prescribed and reviewed medications | N=488 patients (243 IP sites and 245 NP sites) N=7 matched pairs of IP and NP sites (3 podiatrists and 4 physiotherapists) |
| Al Hamarneh et al (2019)37 | Canada, primary care (cardiovascular risk reduction) | Cost-effectiveness analysis (Markov model) | Pharmacist IP | Usual care | Prescribed and reviewed medications | The authors developed their model based on the population observed in the RXEACH trial as follows: N=723 patients (370 in intervention and 353 in control) N=54 pharmacies in the RCT45 |
| Hale et al (2018)38 | Australia, an elective surgery preadmission clinic (venous thromboembolism) | Cost-effectiveness analysis (decision tree model) | Pharmacist IP | Usual care | Prescribed medications | The authors developed their model based on the population observed in an earlier trial as follows: N=384 patients (194 in intervention and 190 in control) N=1 pharmacist prescriber N=59 medical prescribers46 |
| Marra et al (2017)39 | Canada, community care, hospitals or primary care (hypertension) | Cost-effectiveness analysis (Markov model) | Pharmacist IP | Usual care | Prescribed medications | The authors developed their model based on the population observed in the RXACRION trial as follows: N=248 patients (181 in intervention and 67 in control) N=20 pharmacists practised in the community N=2 pharmacists from hospital outpatient clinics N=6 pharmacists from primary care clinics47 |
| i5 Health (2015)42 | England, various settings (eg, primary and secondary care) | Economic analysis of audits, self-reported questionnaires, interviews | IP and SP (for a range of professions, for example, physiotherapists, podiatrists, midwives and radiographers) Community nurse prescribers |
NA | NA | Based on an estimation of the NMP practitioners registered with Northwest England NHS trusts (N=1566 unique prescribers) |
| Courtenay et al (2015)34 | England, primary care (type 2 diabetes) | Mixed-methods and a comparative case study (cost–consequence framework) | Nurse IP | Non-prescribing nurses | Prescribed and reviewed medications, recommended decisions, provided advice and discussed medications with GPs or colleagues | N=12 general practices (6 prescribing nurses and 6 non-prescribing nurses) N=214 patients (131 in nurse prescriber sites and 83 in non-prescriber sites) |
| Neilson et al (2015)40 | UK, primary care (chronic pain) | Regression analysis of costs and effects; the expected value of sample information analysis | Pharmacist IP | Usual care | Prescribed and reviewed medications | N=6 general practices N=125 patients (39 in prescribing, 44 in review and 42 in usual care arms) No information is provided about the number of non-medical prescribers in the two groups |
| Norman et al (2010)41 | UK, primary care (mental health) | Cost–consequences analysis; matched post-test control study | Nurse SP | Usual care | Prescribed medicines | N=90 patients (45 matched pairs) No information is provided about the number of prescribers in the two groups |
GP, general practitioner; IP, independent prescribing; NA, not available; NHS, National Health Service; NMP, non-medical prescribing; NP, non-prescribing; PGD, patient group direction; RCT, randomised controlled trial; SP, supplementary prescribing.