A critical evaluation of available explicit deprescribing tools for their applicability to Indian elderly patients: a scoping review protocol

Abstract

Background

Among the elderly, who are often exposed to polypharmacy, explicit deprescribing tools offer clear, validated guidelines for safely reducing medications. However, the effectiveness of these tools varies across healthcare settings and populations. In India, unique sociocultural and healthcare challenges demand a tailored approach to deprescribing for elderly patients, and the need to adapt existing tools to local contexts. The primary objective of this scoping review is mapping of the contextual relevance and applicability of the existing explicit deprescribing tools for elderly population in Indian healthcare settings.

Methodology

The scoping review will be carried out in six stages: (1) Identifying the review question. (2) Identifying relevant studies through electronic databases (i.e., PubMed, Web of Science, and Embase). (3) Selection of studies to be included based on inclusion and exclusion criteria. Inclusion criteria for this scoping review are studies implementing explicit deprescribing tools involving Indian elderly patients, reporting on outcomes, validation methods, or contextual relevance of deprescribing tools, published in English or non-English language with English translation available. Exclusion criteria for this scoping review are studies focused on implicit deprescribing tools, review articles, case reports, commentaries, and editorials. Two independent reviewers will conduct the search and initial screening of studies. Discrepancies will then be solved through discussion with the third reviewer. (4) Charting, categorizing, and thematic analysis of the extracted data. (5) Collating, summarizing, and reporting the results. (6) Dissemination of findings.

Discussion

By reviewing the patient population and study setting of studies of explicit tools in India, vis a vis the healthcare setting and patient population for which the tool was designed, our scoping review highlighted the strengths and weaknesses in the existing literature. These findings could be used to direct future research and assess the need for a deprescribing tool adapted for the Indian elderly patients.

Background

Polypharmacy, the concurrent use of multiple medications, some of which may be inappropriate, is a common and growing concern among elderly patients, often leading to adverse drug reactions (ADRs), increased healthcare costs, and diminished quality of life [1–4]. Deprescribing is the process of tapering or discontinuing drugs that may no longer be beneficial or may cause harm, and is a critical strategy to mitigate these risks. Several explicit deprescribing tools, e.g., the American Geriatrics Society Beers Criteria® for Potentially Inappropriate Medication Use in Older Adults [5] and the Screening Tool for Older Person’s Prescriptions (STOPP) [6], which provide guidelines and criteria for safely reducing or stopping inappropriate medications, have been developed to assist healthcare providers in this complex task [7–10]. But their applicability and effectiveness can vary significantly across healthcare settings and patient populations. India’s unique sociocultural, economic, and healthcare system factors necessitate a tailored approach to deprescription. To begin with, elderly is defined as 60 years and above in India, as per the National Programme for Health Care of the Elderly (NPHCE) [11], while all current deprescribing tools consider persons over 65 years as elderly. Also, fragmented care is a rule rather than an exception [9]. Busy clinicians often fail to examine all the ongoing prescriptions, and at times, patients end up getting the same medications from two physicians. Patients usually take over-the-counter medications, receive medicines from alternative system of medicine, and take self-prescribed homemade remedies. In addition, not all drugs listed in a deprescribing tool published outside India are available in India, and vice versa, not all inappropriate drugs available and prescribed in India may be listed in an existing tool. This can have implications on conclusions drawn using a tool. This has been highlighted by Chang et al. in 2011, who compared the practicability of six different potentially inappropriate medication (PIM) criteria in geriatric outpatients with polypharmacy in Taiwan and concluded that the prevalence of PIMs varied significantly when different criteria were applied and advised caution in applying PIM criteria developed in other regions when medication availability in the local market is limited [10]. For example, nimesulide, a non-steroidal anti-inflammatory drug banned in children below 12 years, is often prescribed in an adult in India, but is not listed in the Beers Criteria. Also, there is widespread use of fixed dose combinations (FDCs) in India [12], including those containing vitamin and mineral preparations [13]. Most of these FDCs are not included in the existing deprescribing tools.

Thus, there is a pressing need to evaluate the relevance and utility of existing explicit deprescribing tools within the Indian context. A scoping review allows for the exploration of a broad range of literature, including diverse study designs and emerging evidence, often leading to a more specific question which can be addressed through systematic review or meta-analysis. Hence, a scoping review will be the most appropriate methodological approach for this study as it aims to critically evaluate the existing literature regarding explicit deprescribing tools to identify lacunae and areas for future research and tool development for the Indian healthcare context.

Objectives

The primary objectives of this study are as follows:

• To review existing studies of deprescribing conducted in the Indian elderly population in terms of tool used, study population, prescribing and drug use practices, healthcare setting, outcomes, funding sources, and region

• To evaluate the applicability of findings of deprescribing studies in terms of Indian elderly population (age, self-medication, use of alternative medications)

• To evaluate the influence of different healthcare settings and drug availability on the findings of deprescribing studies in India

• To assess the types of outcomes measured (PIM prescription rates, clinical outcomes, cost savings) with deprescribing tools in elderly patients in the included studies

• To identify gaps in literature and propose recommendations for future research and tool development tailored to the Indian context

Methodology

This scoping review will follow the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA-ScR) guidelines to ensure a systematic and transparent approach to identifying and evaluating existing explicit deprescribing tools relevant to the Indian elderly population [14].

The guidelines recommended in PRISMA Extension for Scoping Reviews (PRISMA-ScR) checklist will be followed when reporting the scoping review. There are six stages involved in the scoping review framework which included (1) identifying the review question; (Table 1)(2) identifying relevant studies; (3) selection of studies to be included; (4) charting of information and data from the studies; (5) collating, summarizing, and reporting the results; and (6) conducting consultation of the results with stakeholders and experts).

Table 1.

Table of PCC

Population	Indian elderly population
Concept	Existing studies using explicit deprescribing tools
Context	Studies using explicit deprescribing tool in Indian elderly population for: • Characteristics • Associated outcomes • Relevance and applicability • Gaps and limitations

Stage 1: identifying review questions

Review question: What are the existing gaps in available explicit deprescribing tools relevant to Indian elderly patients?

The sub-questions include:

• What are the characteristics of existing explicit deprescribing tools in the included studies?

• What outcomes are associated with using these tools in elderly patients in the included studies?

• How relevant and applicable are these tools in Indian healthcare settings?

• What gaps and limitations of these tools when applied to the Indian elderly population?

Stage 2: identifying relevant studies

A comprehensive search will be conducted across multiple electronic databases, including PubMed, Web of Science, and Embase. The search will include studies published up to June 2024 and limited to the English language. The search strategy will be developed to ensure it captures all relevant literature and will include keywords and Medical Subject Headings (MeSH) terms related to “deprescribing,” “elderly patients,” “polypharmacy,” and “India.” To ensure a comprehensive and inclusive review, our search strategy will extend beyond peer-reviewed journal articles to include gray literature, including regional Indian repositories such as government health websites, including IndMed, MEDIND, J-Gate, Shodhganga, Indian Citation Index (ICI), Open Government Data (OGD) Platform India, and National Health Portal (NHP) of India. Additionally, recognizing the linguistic diversity in deprescribing research and healthcare guidelines, we will include non-English sources, if English translation is available.

Two independent reviewers will screen the titles and abstracts, followed by screening the full text of all identified studies for eligibility based on predefined inclusion and exclusion criteria:

• Inclusion criteria: Studies implementing explicit deprescribing tools involving Indian elderly patients, reporting on outcomes, validation methods, or contextual relevance of deprescribing tools, published in English and in non-English language if English translation is available

• Exclusion criteria: Studies not involving elderly patients, those focused on implicit deprescribing tools, review articles, case reports, commentaries, and editorials and animal studies (Table 2)

Table 2.

Inclusion/exclusion criteria for study selection

Inclusion criteria	Exclusion criteria
• Studies implementing explicit deprescribing tools in the Indian elderly population • Studies reporting outcomes, validation methods, or contextual relevance of deprescribing tools • Studies published in English or in a non-English language with English translation available	• Studies focused on implicit deprescribing tools • Review articles, case reports, commentaries, and editorials • Studies with full-text article—not available • Animal studies
• Concept: The overarching concept of interest in this scoping review is the explicit deprescribing criteria used for the detection of PIMs in the Indian elderly population, as these criteria were developed by countries outside India • Context: Explicit deprescribing criteria (explicit deprescribing tools include the American Geriatrics Society 2023 Updated AGS Beers Criteria® for Potentially Inappropriate Medication Use in Older Adults [5] and the Screening Tool for Older Person’s Prescriptions (STOPP) version 2, 2023 [6]). In addition, there are drug-specific guidelines or algorithms that provide specific advice on when (or in whom) it is suitable to trial deprescribing a specific medication, or class of medication. They also provide guidance on other parts of the process, such as how to withdraw medications (tapering) and what monitoring is required [15]

Table 3 outlines the concepts. Boolean operators (AND, OR, NOT) will be used to combine search terms within related keywords and is adapted to the syntax used by each database. If there are any search terms missing from the initial search terms, an additional search will be carried out using the updated search terms. Table 4 shows the search strings generated.

Table 3.

List of concepts

Concept 1	Potentially inappropriate medication list, beers criteria, STOPP 2 criteria, STOPP criteria, PIM, PIMs
Concept 2	Aged, elder*, old, older, senior
Concept 3	India, Indian, India*

Table 4.

List of search strings

1	Search string for PubMed	(“potentially inappropriate medication list”[MeSH Terms] OR “beers criteria”[Text Word] OR “STOPP 2 criteria”[Text Word] OR “STOPP criteria”[Text Word] OR “PIM”[Text Word] OR “PIMs”[Text Word]) AND (“Aged”[MeSH Terms] OR “elder*”[Text Word] OR “old”[Text Word] OR “older”[Text Word] OR “Senior”[Text Word]) AND (“India”[MeSH Terms] OR “Indian”[Text Word] OR “India*”[All Fields])
2	Search string for Embase	(“potentially inappropriate medication list” OR “beers criteria” OR “STOPP 2 criteria” OR “STOPP criteria” OR PIM OR PIMs) AND (Aged OR elder* OR old OR older OR Senior) AND (India OR Indian OR India*)
3	Search string for Web of Science	TS = ((“potentially inappropriate medication list” OR “beers criteria” OR “STOPP 2 criteria” OR “STOPP criteria” OR PIM OR PIMs) AND (Aged OR elder* OR old OR older OR Senior) AND (India OR Indian OR India*))
4	Gray literature	Search string will be customized as per source of the literature search

Stage 3: selection of studies to be included

Two independent reviewers will screen the titles and abstracts of all the identified studies using Rayyan (Qatar Computing Research Institute, Doha, Qatar). Full-text articles of potentially relevant studies will be retrieved and assessed for eligibility by two independent reviewers. Any discrepancies will be resolved through discussion or consultation with a third reviewer. Reasons for the exclusion of sources of evidence in the full text that do not meet the inclusion criteria will be recorded and reported in the scoping review. The results of the search and study inclusion process will be reported in detail in the final scoping review and will be presented in a PRISMA flow diagram.

Stage 4: charting of information and data from the studies

Data will be extracted using a standardized data extraction form. The extracted data will include the following:

• Study characteristics (author, year, country, study design)

• Characteristics of the deprescribing tools (name, development process, criteria, and guidelines)

• Outcomes (PIMs, health improvements, adverse drug reaction reductions, quality of life)

• Contextual relevance (sociocultural, economic, healthcare system factors in India)

• Identified gaps and limitations

• I.
  Data cleaning and preparation

  • Compile extracted data in an Excel
  • Review completeness and accuracy of entries, addressing missing or inconsistent data
  • Standardize qualitative responses for consistency in thematic analysis
• II.
  Qualitative analysis

  • A.
    Thematic analysis (using manual coding)

    • Identify common themes:

      • ○ Challenges in applying deprescribing tools in Indian settings—age discrepancy, local drug availability, complementary medicine, FDC prescribing, study settings (inpatient/outpatient, level of healthcare), outcomes (PIMs, cost, clinical outcomes), funding source, region of India
    • Framework analysis using PAGER
      Study results will be categorized under Patterns, Advances, Gaps, Evidence, Research recommendations.
    • Patterns—identifying recurring themes, concepts, or trends in the data
    • Advances—noting any novel contributions or new insights emerging from the literature
    • Gaps—highlighting areas where evidence is missing or underexplored
    • Evidence for practice—extracting practical implications for healthcare, policy, or clinical decision-making
    • Research recommendations—suggesting future research directions based on identified gaps and trends

Stage 5: collating, summarizing, and reporting of results

The extracted data will be synthesized narratively. Descriptive statistics will be used to summarize the characteristics of the included studies and deprescribing tools. The findings will be presented in a tabular and narrative format, highlighting key insights and areas for further research.

• A.
  Visualization

  • Bar charts: To show the frequency distribution of study characteristics using explicit tools by applicability scores
  • Heatmaps: To identify gaps across different evaluation domains
• B.
  Narrative synthesis

  • Key insights regarding studies using explicit deprescribing tool limitations will be summarized.
  • Contextual recommendations will be provided for tool adaptation or development.
• C.
  Interpretation and reporting

  • Findings will be summarized in tables and figures.
  • To account for heterogeneity in terms of target population, study setting, funding source, region, etc., the findings will be synthesized thematically to highlight commonalities while also identifying context-specific differences.
  • Key gaps and future research directions will be discussed—will provide evidence-based recommendations for the deprescribing tools for the Indian elderly population.

Stage 6: dissemination of findings

Study findings will be presented at relevant conferences and published in scientific journals for dissemination of findings which could be useful to develop and adapt deprescribing tool/s at national and regional level, as required.

Limitations

This review recognizes the inherent challenges in comparing deprescribing tools developed within different healthcare systems, as these tools are often shaped by country-specific factors such as prescribing norms, healthcare infrastructure, regulatory policies, and access to medications. Variability in healthcare priorities, provider roles, and patient engagement in deprescribing decisions may further influence tool applicability. To address these challenges, the review will contextualize findings by considering the healthcare settings in which each tool was developed and implemented. This approach will help identify key adaptations required to enhance the relevance of deprescribing tools for elderly patients in the Indian healthcare system (Table 2).

Patient and public involvement

As this scoping review only involves literature-based studies, there is no patient or public involvement.

Authors’ contributions

AS, RJ, SA, AM, and JJC conceptualized the study and prepared a protocol. AS, JJC, RJ, and ST shaped the search strategy. AS, BS, and ST performed database screening. AS, RJ, SA, AM, AF, JJC, and ST drafted the protocol manuscript. AS, RJ, SA, AM, MM, AF, and JJC edited the protocol manuscript. All the authors have reviewed and approved the final manuscript.

Funding

This research is a part of the project funded by the Indian Council of Medical Research, New Delhi, India.

Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

Not applicable. No ethics approval is required as this study only involves reviewing and extracting data from readily available materials.

Consent for publication

All authors have reviewed the article and have given consent for publication.

Competing interests

All the authors have no competing interests.