Best Practices for Data Integrity, Collection and Reporting
Ajay Khanna of Reltio explores the four primary data challenges facing the health care industry today – fragmented data, ever-changing data, privacy and security regulations and patient expectations – and provides advice on how to overcome them while maintaining compliance.
Health care continues to undergo significant transformations. The focus has turned to the overall well-being of a patient rather than one-time treatments. A patient-centric health care approach requires a complete understanding of patients and their behavior, needs and preferences.
Do you have the data to deliver that?
Improving the quality of a patient’s life requires pharma, payers and providers to collaborate closely. Organizations must understand the connections between the patient, physician, provider, payer and prescription. Because of this, reliable data is now at the heart of any health care decision. The quality of data impacts the patient’s health care journey.
In fact, we’re now at the point where it’s unthinkable for any participant of the health care ecosystem to work with incomplete or fragmented data. That prohibits them from deriving meaningful insights and opens doors for compliance risk.
Data Collection: A Messy Problem
Electronic health records (EHRs) are used to capture and manage information collected during patient appointments. Other data sources for patient profiles include personal health records (PHRs) and patient portals, claims and reimbursement information from payers. The health information exchange (HIE) is yet another initiative expediting the movement and consolidation of data between various care partners. Apart from this, many other variables may contribute to health outcomes. These factors may include health behaviors, socioeconomic factors, physical environment, and lifestyle. Such additional data about members and their environment may come from third-party vendors or government sources (e.g., www.healthdata.gov or the Social Security Administration) that can help make better predictions and target interventions to the right patients at the right time. Other data sources also include wearables, fitness monitors and on-body sensors. Data-driven insights and recommendations contribute to improving both quality and efficacy in health care, especially for disease prevention and early identification in the highest risk populations.
As one might imagine, bringing so much data together and using it to make decisions is not without challenges. Fragmented data, ever-changing data, privacy/security regulations and patient expectations are four of the primary data challenges facing the health care industry today.
1. Fragmented Data
Health care data comes from a bewildering number of sources and different formats, such as structured data, paper, digital, pictures, videos, multimedia and so on. Data collection and aggregation communities are equally fragmented, making the extraction and integration of data a real challenge. Providers, payers, public health specialists, employers, social network communities and patients all collect data, but there is no effort to unify the information. There is divergence and duplication of data with no single source of truth. This results in inaccurate and incomplete health care member profiles with little insight into a patient’s well-being journey and a member’s ever-evolving relationship with providers, payers, pharmacy, friends and family members. A lack of understanding, monitoring and support cause low adherence and high readmission risks. Poor communication (particularly during the preoperative phase) often results in cancellation of procedures, causing loss of revenue and inefficient resource utilization.
2. Ever-changing Data
Patients and physicians, like everyone else, move, change their names and professions, retire and die. Payer organizations may also relocate, add new locations or go through various mergers and acquisitions. Moreover, the introduction of new treatments, new drugs and personalized care models change the service delivery and data captured, making it a challenge to keep health care data clean, complete and current. Stale data and information latency directly impact a member’s experience and providers’ business sustainability. The result is a delay in the adoption of new treatment options, inadequate response to health care programs and poor engagement and experience.
3. Privacy and Security Regulations
Maintaining patient trust is the cornerstone for building an efficient health care ecosystem. Data security has become of utmost importance to the health care industry as patient privacy depends on HIPAA2 compliance and secure adoption of electronic health records. Also, with ever-changing regulatory requirements, keeping data sets and engagement compliant can be a challenge. Poor data quality and strategy prevent organizations from meeting new regulatory needs and result in high costs associated with audits and reporting. Until data security and compliance issues are adequately addressed, it’s an uphill task to improve the health of the broader population.
4. Patient Expectations
The health care industry is about to experience the same shift we saw in retail, banking and hospitality. The health care system is on the verge of a perfect storm. A silver tsunami — in the form of the aging baby boomer population – will put the system through a stress test, while pressures from millennials and Generation Z will force health care organizations to choose newer forms of engagement. Health care organizations must equip themselves for a new age, volume and type of members. The industry will need to have an understanding of members’ changing needs and their preferences and then provide solutions that align with their way of life.
A Modern Approach to Data Management
Patients today expect the same experience from health care providers, payers and pharmaceutical companies as they get from retailers and banks: they want to be more involved in their care. They expect all relevant parties, like providers, payers and pharma to collaborate and recommend the best treatment options. Customers and group clients (corporate customers of health care plans) are demanding not just cures for ailments, but wellness and health management programs. Moreover, regulatory agencies like CMS (Centers for Medicare and Medicaid Services) are evaluating health care organizations for the service experience.
Implementing new business models, addressing customer expectations and adopting newer regulations will not be easy, but building a reliable data foundation is the first step toward a patient-centric health care system.
How can data-centric health care organizations overcome these challenges? Health care organizations need a modern approach to data management that brings together information from all sources and helps support all patient-centric initiatives, enabling a complete understanding of patients, physicians, payers and other partners, with real-time visibility into relationships, health metrics and resource utilization trends by the site of care.
A cohesive data strategy blends all patient profile information, including EHR/EMR, lab results, omnichannel interactions, transaction and claims/reimbursement info into a single source of truth, or reliable data foundation, helping health care organizations provide better and more personalized care. This ensures delivery of consistent care and information across all channels, including personal visits, call center inquiries or claims adjudication. All functional groups have the latest and correct patient information. The single source also facilitates quick enablement of new interaction channels so that members can access the required services when and where they want, using the communication channel of their choice. Understanding patient preferences and accurate segmentation helps create targeted programs for a demographic and offers members information tailored to their individual needs. It also helps organize wellness camps and training classes with better response rates.
Health care members and patients are getting more involved in their care and are expecting payers, pharma and providers to collaborate and provide a holistic approach toward wellness. When these entities work together, they can develop much more effective treatment programs with better results. To work together often means securely sharing data. Collaboration requires a Data as a Service strategy, where all parties can safely exchange member information to develop and deliver better therapies and monitor the effectiveness of treatments. A partnership like this is a step toward personalized care and medicine.
Beyond member and patient profiles, health care organizations need to know the complex many-to-many relationships between patients, family members, doctors, caregivers, health care organizations (HCO), locations, payers, plans, products, pharmacies and prescriptions. Relationship information completes the picture. Once the affiliation information is available, health care organizations can make better decisions about a patient’s care and design the treatment options that work best for them.
As patient privacy and compliance are of paramount concern, health care organizations need comprehensive auditing and tracking features to guarantee compliance. Data lineage and a historical trail for any data matched, merged or updated help with traceability. Organizations also need the ability to perform patient record matching, where error and duplicate rates are monitored and rectified and any access to any patient record is captured. With the proper data protection strategies in place, providers can share sensitive patient data securely, both within and across the organization, manage entitled users and adhere to strict monitoring and reporting regulations.
Once the member, patient, provider, payer and plan data are appropriately organized and continuously cleaned and maintained, the next step is to derive relevant and timely insights from the information. The insights must be in the context of the business user. Predictive analytics and machine learning technologies are helping organizations get relevant insights to improve treatment adherence, reduce readmissions and run more impactful preventive and wellness programs. Relevant insights, for example, help uncover aging patients who are nearing the transition from commercial health plan to Medicare programs for timely actions. Providing such members and their physicians with pertinent and timely information helps smooth the transition and improves the service quality and also increases membership numbers.
Health care organizations are aspiring for a patient-centric focus that ensures excellent member experience, adherence to treatment, timely and continued patient engagement to provide relevant health information and regular internal reporting on the quality and cost of the health care. To meet these often-competing objectives, reliable data and up-to-date information must be available at the fingertips of all concerned stakeholders in a compliant fashion. Data-driven applications are making headway in this area, enabling health care organizations to translate vast volumes of data into enterprise assets, driving quality patient care and cost management.
Ajay Khanna is Vice President, Marketing at 
