Understand the Data Quality Check (DQC)

Understanding DQC

1. Data Quality Check for FP Indicator

2. Understanding the Concept of DQC & related processes

3. Part A HIS Framework & Importance of Data Quality

4. Demand for health care services Preferences Information on Client Behavior Price (money, time) Supply of health care services Personnel Facilities Commodities Policy and systems Financing Human resources for health Policy, standards and regulation Health information Logistics Mgt Governance Strategic instruments for Increasing MNCHN/FP service utilization MMR IMR UFM MNCHN/ FP service utilization 4

5. Improved quality of locally generated data Improved planning, policy and decision making at all levels (national, regional, provincial, municipal/city, barangay) Evidence-based interventions made to improve health service delivery performance Achievement of UHC goals: better health outcomes, more equitable financing and more responsive health systems HEALTH INFORMATION SYSTEMS FRAMEWORK

6. The M aternal, N ewborn and C hild H ealth and N utrition ( MNCHN ) continuum Stage Pre-pregnancy Pregnancy Delivery, postpartum & newborn Child Services Family planning Pre-natal, maternal nutrition Safe delivery, postpartum care, newborn care Child nutrition and health care Health and socio-economic outcomes Reduced unplanned & high risk pregnancies; achievement of couple’s desired fertility; reduced population growth; socio-economic development (1) Maternal nutrition & care affecting delivery outcomes; future health of children (2) Reduced maternal mortality; neonatal mortality (3) Child nutrition and health affecting survival & future health and socio-economic outcomes (4) CSR Data w/c will serve as bases for these interventions should be valid and reliable

7. The M aternal, N ewborn and C hild H ealth and N utrition ( MNCHN ) Strategy Stage Pre-pregnancy Pregnancy Delivery, postpartum & newborn Child Services Family planning Pre-natal, maternal nutrition Safe delivery, postpartum care, newborn care Child nutrition and health care Health and socio-economic outcomes Reduced unplanned & high risk pregnancies; achievement of couple’s desired fertility; reduced population growth; socio-economic development Maternal nutrition & care affecting delivery outcomes; future health of children Reduced maternal mortality; neonatal mortality Child nutrition and health affecting survival & future health and socio-economic outcomes CPR ANC 4 SBA, FBD, EBF FIC, micro-nutrient supplementation

8. Field Health Service Information System (FHSIS) To support the management of local and nationwide health service delivery & interventions To provide the basic service data needed to monitor activities of each health program, including family planning (FP)

9. Field Health Service Information System (FHSIS) Part of the system of the designated statistics – as provided for under Executive Order 352 Only information system implemented down to the barangay level

10. Importance of FHSIS to local decision-making EO 342 designates FHSIS as part of the Philippines official statistics of the government FHSIS is the only system that provides data on health service delivery indicators at the barangay, municipality/city, provincial, regional and national levels Planning for focused health interventions , resource allocation, and policy development depend on the reliability and validity of FHSIS

11. What is “data quality check” (DQC)? Involves a step-by-step process of correctly applying the definition, formula and recording and reporting processes as contained in DOH FHSIS Manual of Operations This process has helped uncover different sources of inaccuracies in reported FHSIS statistics Provides a systematic approach for identifying and addressing these sources of inaccuracies in key FP and MCH indicators of FHSIS

12. In collaboration with NCDPC and EB, USAID supported the development “Data Quality Check” in 2010 based on FHSIS Manual of Operations 2008 in response to observations of unexpectedly high forecast of commodity requirements during the formulation of PIPH Tested, improved and reviewed by the DOH and LGUs DOH suggested to expand the DQC tool to include other key MCH indicators, namely, ANC4, SBA, FBD, EBF, FIC and Vitamin A supplementation DQC was institutionalized and incorporated into the DOH’s Manual of Operations for MNCHN/FP (2nd Edition, May 27, 2011) DQC updated to reflect changes in the updated FHSIS Manual of Operations 2012 . Changes include new definitions and formula of some indicators and changes in TCL and reporting forms. DQC (FP)updated to reflect changes in the updated FHSIS Manual of Operations 2018

13. Examples of reported and corrected data Source: USAID LuzonHealth Project Source: LuzonHealth Project

14. Source: USAID LuzonHealth Project Source: LuzonHealth Project

15. Examples of reported and corrected data Source: USAID LuzonHealth Project Source: LuzonHealth Project

16. Examples of reported and corrected data Source: USAID LuzonHealth Project Source: LuzonHealth Project

17. Source: USAID LuzonHealth Project Source: LuzonHealth Project

18. Reliable data to forecast commodity and service requirements Provided a stronger basis for improving service delivery Realization that not only does improved data quality helps LGUs plan and implement programs better, but that by improving service delivery, the quality of their data also improves. Realization that new sets of information from the FHSIS can be extracted for new programs such as information on adolescents and services provided to them Usefulness of the DQC’d FHSIS data for LGUs

19. Commitment to sustained DQC implementation National, regional and LGU partners commitment to DQC: National : Integration into the MNCHN MOP 2011; Nationwide capacity building DOH Regional Offices : Refresher Course and support to LGU roll-out in LGU : Signed Executive Order on sustained implementation of DQC for health systems strengthening Further commitment needed from National Agencies Inter-agency commitment (DOH, DILG, and NEDA) to reliable and comparable local data for assessment of LGU performance Use of DQC tool to improve quality of data reported in LGU Scorecard

20. Source: LuzonHealth Project

21. Detailed Steps in Conducting Data Quality Check for FP (DQC for FP)

22. Part B1 Quick Review of FHSIS Forms

23. Recording & Reporting Forms for FP Level Recording Forms Reporting Forms BHS – Midwife Health Center – Midwife/Nurse Masterlist of WRA and Adolescent Women for FP Services FP Form 1 FP Target Client List Summary Table M1 RHU/City Health Office Monthly Consolidation Table Q1

24. Masterlist of WRA and Adolescent Women 10-14 years old Form used to extract data on women with unmet need for family planning

25. WHAT IS WRA MASTERLIST FORM? Recording form aimed at generating basic information about women of reproductive age and who among them have unmet need for FP. BHS midwives and community health workers and other volunteers are expected to conduct the WRA masterlisting at least annually. Identified WRA with unmet need for FP are visited, provided with FP infor and encouraged to go through 1-1 counselling and provided with FP services/methods of their choice

26. Masterlist of WRA

27. FP FORM 1

28. FP Form 1

29. WHAT IS FP FORM 1 Form 1 records the demographic-socio-economic profile of the client, their medical & obstetrical history as well as the presence of risks for sexually transmitted infections and violence against women. It also records the results of physical examination undertaken. At the bottom of the front page is a space for the signature of the client, and the guardian (for those below 18 rs old) The back-side is where the service provider records the medical findings during each visit, the FP method accepted and the date of follow-up with the name and signature of the service provider.

30. Guide

31. FP Target Client List

32. FP Target Client List

33. WHAT IS THE TARGET CLIENT LIST Recording form containing the list o FP clients which allows the midwives to systematically organize, plan and document FP service performance monthly, quarterly and annually Helps in tracking and monitoring FP services; helps in planning and carrying out patient care and FP service delivery (including FP counselling provided to patients) Serves as the source document for the official reports that need to be submitted by the facility (source of M1)

34. ALTERNATIVE WAY OF ORGANIZING & PRESENTING THE TCL

35. FP Target Client List

36. Drop-out: Pills A client is considered drop-out from the method if she: fails to re-supply from the last 21 white pill up to the last brown pill (if the pills have a set of brown tablets/iron); or within the last seven (7) days gets supply or transfers to another provider or clinic. in this case, the client is listed under the Other Acceptor (“Changed Clinic”) in the clinic where she transferred and a drop-out in her former clinic. decides to stop the use of pills for any reason Note: The service provider should undertake a follow-up visit of the client during the above period before dropping her from the method.  

37. Drop-out: Injectables A client is considered a drop-out if she: for DMPA – every 3 months: fails to visit the clinic on the scheduled date of visit up to the last day of 4 weeks after the scheduled date of visit for NET-EN – every 2 months: fails to visit the clinic on the scheduled date of visit up to the last day of 2 weeks after the scheduled date of visit gets supply or transfers to another provider. The client is listed under the Other Acceptor (“Changed Clinic”) in the clinic where she transferred and a drop-out in her former clinic stops receiving injection for any reason Note: the service provider should undertake a follow-up visit within this above period before dropping her from the method.

38. Drop-out: IUD A client is considered a drop-out if she: decides to have the IUD removed has expelled IUD that was not re-inserted did not return on the scheduled date of follow-up visit within three (3) to six (6) weeks after insertion If the client has not followed up for 2 years after initial follow-up visit or after effectivity date of IUD Note: Follow-up of the client within the week of the scheduled visit should be done before dropping her out from the method  

39. Drop-out: Implant A client is considered a drop-out if she did not return to the facility 3 years after the implant insertion for removal and replacement of the implant rod. Note: The service provider should undertake a follow-up visit during the above period prior to dropping her out from the method.

40. Drop-out: BTL A client is considered drop-out if she: reaches the age of 50 years reaches menopause underwent procedure like hysterectomy or bilateral salpingo -oophorectomy Note: The service provider should undertake a follow-up visit during the above period prior to dropping her out from the method.  

41. Drop-out: Condom A client is considered a drop-out if she: fails to return for re-supply on scheduled visit gets supply from another clinic (change clinic) decides not to use condom for any reason  

42. Drop-out: NFP-LAM A client is considered a drop-out if she does NOT fulfill ANY of the following criteria: Mother has no menstruation or amenorrheic within six months. Spotting or bleeding during the last fifty-six (56) days postpartum is not considered return of menses. Fully/exclusive breastfeeding which means: No other liquid or solid except breast milk is given to the infant, Intervals should not exceed four (4) hours during the day and six (6) hours at night. Baby is less than six (6) months  

43. Drop-out: NFP-SDM A client is considered a drop-out if she: fails to return on the follow-up date to check on the proper use of the method if the client fails to identify her own fertile and infertile periods if the user has no indication of SDM use through beads or no knowledge of first day of menstruation or cycle length decides to stop the use of the method Note: The service provider should undertake a follow-up visit during the above period prior to dropping her out from the method.

44. Drop-out: NFP-BBT/CMM/STM For Basal Body Temperature/Cervical Mucus Method/ Symptothermal Method A client is considered a drop-out if client: fails to return on the follow-up date to check on the correct charting and/or the proper use of the method fails to identify her own fertile and infertile periods decides to stop the method Note: Client is given a period of time (2 months) as a learning user to practice correct charting with assistance before recording the client as a new acceptor. A new acceptor is considered if the client can identify and chart her fertile and infertile period correctly.

45. Summary Table for FP

46. Summary Table

47. Monthly Report for FP (M1)

48. Monthly Consolidation Table

49. Monthly Consolidation Table

50. Guide

51. Quarterly Report for FP (Q1)

52. Part B2 Detailed Steps in Conducting Data Quality Check for FP (DQC for FP)

53. Ensure that you have the following: M1 (Current Month and Previous Month) FP TCLs Worksheet Ruler Pencil Calculator Other relevant records From notebooks, etc

54. M1 TCL Compute PREVIOUS PREVIOUS PRESENT PRESENT TCL

55. Step 1. Check FP Method COUNT ALL THAT ARE LISTED

56. COLUMN A

57. Check if the CU Beginning of the Month of the Current Month’s M1 (Ex. Dec 2019) reflect s the CU End-of-Month (Ex. Nov 2019) of the previous M1 Report Remember: COLUMN A: FPCU Beginning of December = is EQUAL to FPCU End of November

58. COLUMN B

59. Column B: C ount the FP Current Users listed in the TCLs as of end of Nov ember Count from TCL

60. Steps in Counting FP CU for Column A (do not dropout yet)

61. COLUMN C: LISTED IN THE TCL BUT NOT REPORTED

62. Column C: Compute for No of CU listed in the TCL & provided with services but not reported C =B-A if B>A If B<A, please proceed to Column D B - A = C

63. COLUMN D

64. Column D: Compute for No of CU reported in numbers ,but not listed (no names) in the TCL D =A-B if A> B If A=B, no need to process Columns C and D (just indicate “0”)

65. Column E : Count the NEW ACCEPTORS (November) Date of Registration Age Type of Client Previous Method Follow-up Visit

66. COLUMN E: Count NEW ACCEPTORS of (November) Date of Registration (November) Age Type of Client Identify NA through date indicated Previous Method

67. Column F : Count OTHER ACCEPTORS (December) Date of Registration Age Type of Client Previous Method Follow-up Visit Count the number of Other Acceptors

68. Column F: Count OTHER ACCEPTORS (December) Date of Registration (December) Age Type of Client Identify the Other Acceptors (CM,CC,RS) Previous Method

69. COLUMN G: DROP-OUTS

70. Column G: Identify clients that need to be DROPPED OUT in December –includes current and missed dropouts REFER TO DROPOUT CRITERIA PER METHOD Steps: Age (NOT >49yo) Follow-up visit Remarks

71. DROPOUT if AGE is > 49 years old 2/10/1970 49 Date of Registration (1) (mm/dd/yy) Family Planning Serial No.(2) Client Name (3) Address (4) Age Birthdate (5) 1/22/2019 70 Daquia, Lena Block 1, Lot 21, Barangay Narra 2/19/2019 72 Felizar, Hazel Block 1, Lot 2, Barangay Narra 1/1/1967 52 1/26/2019 71 Rama, Elena Block 1, Lot 3, Barangay Narra 12/5/1969 50 Recheck birthday vs. date of follow-up visit

72. DROPOUT if NO FOLLOW UP VISIT Accomplish DROPOUT COLUMN 1st 2nd 3rd 4th 5th 6th 7th 8th 9th 10th 11th 12th Date Reason*** 1/29/19 1/29/19 2/2/19 2/2/19 2/26/19 2/26/19 Follow up Visits (9) (Upper Space: Next Service Date / Lower Space: Date Accomplished) Drop-Outs (10)

73. Check dropout and remarks column , count all dropouts for December, and those that should have been dropped out for the previous months 1st 2nd 3rd 4th 5th 6th 7th 8th 9th 10th 11th 12th Date Reason*** 2/27/19 3/27/19 4/24/19 5/22/19 6/19/190 7/17/19 2/27/19 3/26/19 4/23/19 5/21/19 6/18/19 7/16/19 2/27/19 3/27/19 4/24/19 5/22/19 6/19/19 7/17/19 8/14/19 9/11/19 10/9/19 11/6/19 2/27/19 3/26/19 4/23/19 5/21/19 6/18/19 7/16/19 8/13/19 9/10/19 10/8/19 Follow up Visits (9) (Upper Space: Next Service Date / Lower Space: Date Accomplished) Remarks (11) Drop-Outs (10) B Baby was given Juice 12/27/19 MISSED DROPOUT DROPPED OUT IN DECEMBER

74. COLUMN H

75. Compute Column G: Current Users End Month Of DECEMBER A +C -D +E +F =H -G Compute for CU end of Month

76. Identify Areas for Improvement Method Accepted (6) LAM LAM LAM Date of Registration (1) (mm/dd/yy) Family Planning Serial No.(2) Client Name (3) Address (4) Age Birthdate (5) Previous Method (8) 1/30/2019 47 Adelantado, Adriana Block 1, Lot 21, Barangay Sampaguita 6/30/1981 38 CU NONE Type of Client (7) 1/30/2019 48 Matabunkay, Cecille Block 1, Lot 3, Barangay Sampaguita 12/30/1983 36 CU NONE 2/25/2019 49 Halagor, Indira Block 1, Lot 2, Barangay Sampaguita 1/15/1991 28 CU NONE Complete Information Updated Age Correct Accomplishment of TCL

77. 7. Accomplish the remarks column REMARKS: Reason for dropout Most common reason of discrepancy Areas for improvement

78. COLUMN I: Record the New Acceptor of the Current Month Identify the NA of the Present Month

79. SUBMIT THE CORRECTED M1

80. Other Innovative Support that can be Provided to BARMM

81. OTHER INNOVATIVE SUPPORT FOR LOCAL FHSIS IMPLEMENTATION THAT CAN BE PROVIDED TO BARMM Use of (old-school) age disaggregated form ALTERNATIVE WAY OF ORGANIZING TCL BY AGE GROUP, CONSISTENT WITH M1 REPORT

82. OTHER INNOVATIVE SUPPORT FOR LOCAL FHSIS IMPLEMENTATION THAT CAN BE PROVIDED TO BARMM Use of Excel-based Electronic M1 & Q1 forms to avoid computational mistakes

83. DAY 2 DQC TRAINING SESSION: Review of the DQC Process Data Flow, Submission Timelines DQC Exercises Kahoot! 

84. UNDERSTAND FHSIS & DQC CONCEPTS& BUILD CURRENT SKILLS EFFECTIVELY PROVIDE THE TA AND BUILD LGU SKILLS SECURE LGU/RHU/HC/BHS COMMITMENT TO CORRECT/ UPDATE THEIR TCLs/M1 and SUSTAIN the REGULAR CONDUCT OF DQC TO MAINTAIN DATA QUALITY ADVOCATE FOR THE LGU TO ENSURE THAT SUCH CLEAN DATA IS UTILIZED FOR DECISION-MAKING, PLANNING, & BUDGETING & IMPLEMENTING KEY INTERVENTIONS ENSURE COMMODITY SECURITY INCREASING FP SERVICE UTILIZATION SUSTAINED FINANCING FOR FP

85. Part III Data Flow, Submission Timelines, Familiarity with the Forms (DQC for FP)

86. Flow of FHSIS Data Collection, Consolidation & Reporting

87. Timelines of Submission

88. Timelines of Submission