Abstract
Background. Clinical documentation improvement is a process designed to accurately represent the severity of illness and patient care needs by thoroughly documenting diagnoses, comorbidities, complications, and services provided, thereby supporting the coding system. By ensuring precise cost calculations, the coding system helps prevent insurance deductions caused by incomplete hospital documentation. This policy brief aims to propose solutions that establish a framework for enhancing clinical documentation to reduce insurance denials.
Methods. This policy brief is based on evidence from a mixed-methods study and a literature review conducted across the Scopus, PubMed, ISI, SID and Magiran databases. Additionally, interviews were conducted to gather internal evidence. Subsequently, policy options were evaluated through a focus group discussion with seven experts—two instructors from Health Information Management, two from Medical Informatics, and three from the Health Information Management department. These options were then ranked based on their benefits, disadvantages, and feasibility.
Results. Policy alternatives include unifying clinical documentation guidelines, training clinical specialists, conducting periodic assessments of documentation with feedback, establishing incentives, preparing for the implementation of the DRG system, and utilizing artificial intelligence–based technology tools.
Conclusion. Given the importance of accurate clinical documentation in reducing insurance denials, it is recommended that physicians receive appropriate training after the necessary infrastructure has been established and clinical documentation guidelines have been standardized. Medical record documentation should be evaluated at predetermined intervals, with feedback and designated incentives provided.
Extended Abstract
Background
Clinical documentation improvement (CDI) plays a vital role in healthcare organizations. Accurate clinical documentation supports patient care, coding, billing, and appropriate reimbursement. These programs are essential for enhancing patient care, financial performance, and regulatory compliance. Common clinical documentation errors include missing written medical orders for services provided, reports lacking sufficient detail, inadequate justification of medical necessity, discrepancies between physician orders and nursing reports of medications or supplies, and incomplete documentation of all services rendered. Poor documentation not only undermines payment processes but also compromises patient care, clinical research, legal proceedings, quality improvement audits, and future applications of artificial intelligence and machine learning. Implementing a clinical documentation improvement program to reduce insurance denials generates high-quality, reliable data, thereby improving medical record documentation. This policy brief employs evidence-based strategies and draws on effective national and international experiences to enhance clinical documentation and reduce insurance denials.
Methods
The study employed a mixed-methods design, combining a literature review, interviews, and a focus group. Initially, a literature review was conducted using the Scopus, PubMed, ISI, SID, and Magiran databases with the keywords "clinical documentation," "improving clinical documentation," and "reducing insurance deductions." The review included articles that addressed issues related to clinical documentation and strategies for its improvement. These findings were supplemented by 17 semi-structured, in-depth interviews conducted in person at locations agreed upon with the participants. An interview guide, developed based on the research objectives and previous studies, guided the discussions. The interview questions focused on identifying problems with clinical documentation and proposing solutions to enhance medical record documentation in a multidisciplinary hospital setting. All data collected were stored and analyzed anonymously to ensure participant confidentiality. Content analysis was employed to analyze the data: notes were read multiple times to gain a comprehensive understanding, followed by a line-by-line review of the transcripts in Word. Concepts were then extracted from participants' statements and categorized into main and general themes. Finally, potentially effective policy options were identified based on responses from the initial interviews and the literature review.
In the next step, the focus group method was employed to prioritize these policy recommendations. The recommendations were discussed and reviewed with the participation of seven experts: two members of the Scientific Board of Health Information Management, two faculty members of Medical Informatics with medical degrees, and three staff members from the Health Information Management department. Policy options were evaluated and prioritized based on their advantages and disadvantages, feasibility, and potential implementation barriers.
Result
Policy Options:
1. Developing a policy to unify clinical documentation guidelines
The Ministry of Health and Treatment, in collaboration with insurance organizations, should unify existing documentation guidelines and develop clinical documentation standards, as no single format is suitable for all clinical specialties. Therefore, clinical specialists should establish their own specific guidelines and use them as standard references for clinical documentation in the records of both organizations.
2. Training and Empowering Clinical Specialists
The Medical and Specialty Education Council can develop course units for residents as part of the curriculum review for clinical specialties. The General Directorate of Continuing Medical Education can organize these courses for practicing physicians. Additionally, the heads of other clinical groups, such as nursing, can organize similar workshops during internship periods.
3. Evaluating Clinical Documentation and Providing Feedback
To implement this policy, it is recommended to first design appropriate evaluation tools, followed by providing the necessary training to assess and analyze the results. Both internal and external evaluations of clinical documentation quality should be conducted regularly, with timely and constructive feedback given to physicians.
4. Developing Incentive and Motivation Policies
Hospital administrators at the university level can acknowledge the performance of active physicians by offering financial and non-financial rewards, presenting certificates of appreciation, granting incentive leave, or increasing bonuses. Additionally, the Department of Treatment recognizes these physicians for their efforts in improving clinical documentation by hosting annual celebrations.
5. Develop a Policy for the Preliminary Implementation of the Diagnosis-Related Groups (DRG) System
This policy must be implemented with the agreement of the Ministry of Health and insurance organizations. To facilitate the DRG payment system, it is recommended to acquire the Grouper software, localize it, and pilot it in several hospitals. Concurrently, it is essential to establish the system's infrastructure, including staff training and the documentation requirements for medical records.
6. Utilizing AI-Based Technological Tools
Hospital administrators at the university level can utilize natural language processing technologies, such as speech recognition, to document surgical reports, pathology reports, radiology reports, and progress notes. Additionally, AI tools can extract specialized elements through text mining and use them to analyze and manage clinical documentation and assigned codes.
Conclusion
Hospitals face significant challenges in managing multiple insurance companies, each with distinct and sometimes conflicting rules, regulations, and tariffs. This complexity increases the cognitive load on staff and raises the likelihood of errors. Integrating existing guidelines and developing clinical guidelines within the Ministry of Health and insurance organizations represents an appropriate initial step toward implementing Clinical Documentation Improvement (CDI) programs.
The accurate documentation of patients' demographic, clinical, and financial data is crucial for implementing the DRG payment system and improving the transparency of clinical and financial information in healthcare. Naderi notes that the national health information system has significantly advanced through optimized processes, improved quality of clinical documentation, and greater accuracy in recording diagnostic and therapeutic codes, as well as cost information.
Ongoing education for healthcare professionals has been emphasized as the primary strategy for improving clinical documentation in all previous studies. Prior research indicates that medical students receive minimal formal training in clinical documentation, with most learning occurring in practical settings. Therefore, it is recommended that residents receive formal training through the creation of a dedicated course unit.
Previous studies have identified clinical documentation assessment and feedback as the most important recommendations for improving clinical documentation. Developing appropriate assessment tools has been highlighted as a key requirement for implementing this policy. To support this policy, various assessment instruments have been proposed, including structured clinical forms, medical record reviews, audit checklists, and simulators. Research has demonstrated that documentation assessment combined with personalized feedback, especially when integrated with other policy measures such as training, the development of structured clinical forms, or the redesign of electronic forms, is an effective approach to enhancing clinical documentation.
Implementing financial and nonfinancial incentives, along with providing positive feedback, enhances physicians' documentation performance. Given physicians' dissatisfaction with the time spent documenting medical records, it is likely that these challenges will be addressed in the future through the use of natural language processing and artificial intelligence technologies. However, before deploying these tools, the models must be extensively refined to ensure that their benefits outweigh their drawbacks. Furthermore, additional research is needed to explore the legal and ethical implications of employing these technologies in clinical documentation.
Practical Implications of the Research
The results of this research can inform the development of policies aimed at improving clinical documentation at both regional and national levels. Implementing a combination of policy options will enhance clinical documentation and generate high-quality, reliable data. This improvement will not only increase reimbursement for patient services but also reduce medical errors, diagnostic inaccuracies, and legal risks, ultimately enhancing patient safety. Investing in Clinical Documentation Improvement (CDI) programs is a critical step for the hospital’s future, as it provides dependable data for clinical research, management analysis, and machine learning applications.