Harvard Case - Predicting Net Promoter Score (NPS) to Improve Patient Experience at Manipal Hospitals
"Predicting Net Promoter Score (NPS) to Improve Patient Experience at Manipal Hospitals" Harvard business case study is written by Rahul Kumar, Sandhya Shenoy, Unnikrishnan Dinesh Kumar. It deals with the challenges in the field of Marketing. The case study is 11 page(s) long and it was first published on : Sep 1, 2017
At Fern Fort University, we recommend Manipal Hospitals implement a comprehensive strategy to leverage AI and machine learning to predict Net Promoter Score (NPS) and improve patient experience. This strategy will involve a multi-pronged approach incorporating data analysis, customer journey mapping, and targeted interventions.
2. Background
Manipal Hospitals, a leading healthcare provider in India, faces the challenge of improving patient satisfaction and loyalty. The case study highlights the importance of Net Promoter Score (NPS) as a key indicator of patient experience. Manipal Hospitals seeks to understand the factors influencing NPS and develop a predictive model to proactively address potential issues and enhance patient satisfaction.
The main protagonists of the case study are the management team at Manipal Hospitals, who are tasked with improving patient experience and driving business growth. They are seeking to leverage data and analytics to achieve this goal.
3. Analysis of the Case Study
To analyze the case study, we will utilize the following frameworks:
1. Customer Journey Mapping: This framework will help us understand the touchpoints of the patient journey and identify areas where improvements can be made.
2. SWOT Analysis: This framework will help us identify the strengths, weaknesses, opportunities, and threats associated with Manipal Hospitals' current situation.
3. Marketing Mix (4Ps): This framework will help us analyze the current marketing mix and identify opportunities for improvement.
4. AI and Machine Learning: This framework will help us understand how AI and machine learning can be used to predict NPS and improve patient experience.
Analysis:
- Customer Journey Mapping: The patient journey at Manipal Hospitals can be mapped from initial consultation to post-treatment follow-up. Key touchpoints include:
- Pre-Hospitalization: Initial consultation, appointment scheduling, pre-admission tests, and communication with the hospital.
- Hospitalization: Admission process, interaction with medical staff, room comfort, food quality, and discharge process.
- Post-Hospitalization: Follow-up appointments, medication management, and communication with the hospital.
- SWOT Analysis:
- Strengths: Strong brand reputation, experienced medical staff, advanced medical technology, and a focus on patient care.
- Weaknesses: Limited use of data analytics, lack of a centralized patient experience management system, and inconsistent service quality.
- Opportunities: Leverage AI and machine learning to predict NPS, improve patient communication, personalize care, and optimize operational efficiency.
- Threats: Increasing competition from other healthcare providers, changing patient expectations, and rising healthcare costs.
- Marketing Mix (4Ps):
- Product: Manipal Hospitals offers a wide range of healthcare services, including inpatient and outpatient care, surgery, and specialized treatments.
- Price: Pricing strategies vary based on the type of service and patient demographics.
- Place: Manipal Hospitals has a network of hospitals and clinics across India, providing convenient access to care.
- Promotion: Marketing efforts include advertising, public relations, social media engagement, and patient referral programs.
- AI and Machine Learning: AI and machine learning can be used to analyze patient data and predict NPS by identifying key drivers of patient satisfaction and dissatisfaction. This data can be used to develop targeted interventions to improve patient experience.
4. Recommendations
1. Develop a Data-Driven Patient Experience Management System:
- Implement a centralized system to collect and analyze patient data from various touchpoints, including patient surveys, medical records, and feedback channels.
- Utilize AI and machine learning algorithms to identify patterns and predict NPS based on patient demographics, medical history, and service interactions.
2. Implement Targeted Interventions to Improve Patient Experience:
- Use predictive analytics to identify patients at risk of low NPS scores and proactively address their concerns.
- Develop personalized communication strategies based on patient preferences and needs.
- Implement targeted training programs for staff to improve service quality and address specific patient concerns.
3. Enhance Patient Communication and Transparency:
- Utilize digital channels, such as mobile apps and online portals, to provide patients with real-time updates on their treatment progress and access to medical records.
- Implement patient education programs to improve understanding of medical conditions and treatment options.
- Foster open communication between patients and medical staff to address concerns and improve satisfaction.
4. Leverage Marketing and Digital Strategies:
- Utilize digital marketing channels to reach target audiences and promote the hospital's services.
- Develop targeted content marketing campaigns to educate patients about specific medical conditions and treatment options.
- Implement social media listening tools to monitor patient feedback and address concerns promptly.
5. Foster a Culture of Continuous Improvement:
- Regularly review and analyze patient feedback to identify areas for improvement.
- Implement a system for tracking and measuring the impact of interventions on NPS scores.
- Encourage staff to actively participate in improving patient experience through training and feedback mechanisms.
5. Basis of Recommendations
These recommendations are based on the following considerations:
- Core competencies and consistency with mission: Manipal Hospitals' mission is to provide high-quality healthcare services and enhance patient experience. These recommendations align with this mission by leveraging technology and data to improve patient care.
- External customers and internal clients: The recommendations focus on improving the experience of both external customers (patients) and internal clients (staff) by providing them with the necessary tools and resources.
- Competitors: The recommendations are designed to help Manipal Hospitals stay ahead of the competition by embracing innovation and utilizing data-driven approaches to improve patient experience.
- Attractiveness ' quantitative measures: The use of AI and machine learning to predict NPS and improve patient experience is expected to lead to increased patient satisfaction, loyalty, and revenue.
6. Conclusion
By implementing these recommendations, Manipal Hospitals can leverage AI and machine learning to predict NPS and improve patient experience. This will lead to increased patient satisfaction, loyalty, and revenue, ultimately strengthening the hospital's position in the competitive healthcare market.
7. Discussion
Other alternatives not selected include:
- Traditional survey-based approach: This approach relies on periodic surveys to collect patient feedback, which can be time-consuming and may not provide real-time insights.
- Focus on operational efficiency: While operational efficiency is important, it should not come at the expense of patient experience.
Risks and Key Assumptions:
- Data quality and availability: The success of the recommendations depends on the quality and availability of patient data.
- AI and machine learning expertise: Manipal Hospitals will need to invest in AI and machine learning expertise to implement the recommendations effectively.
- Patient acceptance: Patients may be hesitant to share their data or participate in AI-powered interventions.
8. Next Steps
- Phase 1 (Short-term): Conduct a pilot study to test the effectiveness of AI and machine learning in predicting NPS.
- Phase 2 (Mid-term): Implement a centralized patient experience management system and develop targeted interventions based on data analysis.
- Phase 3 (Long-term): Continuously monitor and improve the system based on patient feedback and data analysis.
By taking these steps, Manipal Hospitals can successfully leverage AI and machine learning to predict NPS and improve patient experience, ultimately achieving its goal of becoming a leading healthcare provider in India.
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Case Description
Manipal Hospitals, which was started in 1953, had the advantage of being the "oldest" healthcare group in India. In six decades, the group could establish the reputation for being ethical and patient friendly. In 2017, Manipal Hospitals catered to around 2 million customers from India and overseas every year through their tertiary and secondary care facilities. In 2017, MHE managed an aggregate of 5,200 plus beds among 16 hospitals, over 13 locations across 6 states in India and one hospital in Klang, Malaysia. The Group's acute care flagship quaternary care facility located in the heart of Bangalore, India's IT capital was set up in 1991. The 680-bed Manipal Hospital at HAL Airport Road provided care in over 60 specialties under one roof. Ajay Bakshi, MD and CEO of Manipal Hospitals strongly believed that the word-of-mouth (WOM) is much stronger than any other type of promotion and thus it is important for MHE to keep customers informed about the improvements. With the improved system for feedback collection, he was confident of moving towards a more tangible outcome from feedback collection. Collecting Net Promoters Score (NPS) and tracking the trend of NPS was an integral part of patient care at MHE. He also believed that closing the loop is a central theme of the Net Promoter Score and thus NPS should be pivotal to understanding the deficiencies in the system and improving it. Ajay believed that NPS score itself is just the tip of the iceberg. The real value was provided by understanding what leads to the NPS score, especially the causes of detractors and promoters and asking follow-up questions on the reason for the score. It provided a gold mine of information which can be used to improve patient care.
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